Wireless Ad hoc Network



Today there are numerous portable devices such as laptops, mobile phones, PDAs (Personal Digital Assistants) and MP3 players which are used by the professional and private lives of the individuals. Mostly these devices are used separately for specific purpose. A Network is a collection of nodes which are highly interconnected. This interconnection can be wired, wireless or wired cum wireless. Mobile devices coupled with wireless network interfaces is an essential part of computing environment that consist of infra-structured and infrastructure-less mobile networks. Wireless Local Area Network (WLAN) is the most prevalent infra-structured mobile network which is based on IEEE 802.11 standard, where a mobile node communicates with a fixed base station, and thus a wireless link is limited to one hop between the node and the base station. Mobile Ad hoc Network (MANET) is an infrastructure less multihop network where each node communicates with each other either directly or indirectly through intermediate nodes [1].
There are two variations of mobile wireless networks, the first is known as infrastructured network i.e. a network with fixed and wired gateways. The second is known as infrastructureless network or an ad hoc network. Ad hoc networks have no fixed routers, all nodes can be connected dynamically and all are capable of movement in an arbitrary manner.
Energy efficiency is one of the most important issue for wireless ad hoc networks and regarding this issue, a lot of research has been made. In this chapter wireless ad hoc networks has been introduced. Furthermore, routing protocol has been described and last energy management protocols has been described for wireless ad hoc networks.
A wireless adhoc network is a collection of two or more devices equipped with wireless communications and networking capability as shown in Figure 1.1. Such devices can communicate with another node that is immediately within their radio range or one that is outside their radio range. For the latter scenario, an intermediate node is used to relay or forward the packet from the source toward the destination [2]. An adhoc wireless network is self-organizing and adaptive. This means that a formed network can be de-formed on-the-fly without the need for any system administration. The term 'ad-hoc' tends to imply 'can take different forms' and 'can be mobile or networked.' Adhoc nodes or devices should be able to detect the presence of other such devices and to perform the necessary handshaking to allow communication and sharing of information and services.

Figure 1.1: Wireless Ad hoc Network

Ad hoc networks which are also known as mesh networks. This networks are defined by the manner in which the networks nodes are organized to provide paths for accessing the data to be routed from the user to and from the desired destination. Ad hoc has two definition, the first one- 'impromptu' or 'using what is on hand' and the second one is- 'for one specific purpose'. Ad hoc networks follows both definitions, as well. So, they are formed as they are needed and they use the resources on hand, and are configured to handle exactly what is needed by each users for 'one specific purpose' [3].

The most important concern for wireless adhoc network is routing protocols. Routing protocols must deal with the typical limitations of these networks, which include high power consumption, low bandwidth, and high error rates. These routing protocols may generally be categorized as table-driven approach and source-initiated on-demand-driven approach as shown in Figure 1.2.

Table-Driven Routing Protocols (TDRP) attempt to maintain consistent, up-to-date routing information from each node to every other nodes in the network. These protocols require each node to maintain one or more tables to store routing information, and they respond to changes in network topology by propagating route updates throughout the network to maintain a consistent network view. The areas in which they differ are the necessary routing tables and the methods by which changes in network structure are broadcast. TDRP can be classified further as Distance Sequenced Distance Vector (DSDV), Wireless Routing Protocol (WRP), and Cluster Switch Gateway Routing (CSGR) [4]. In the following sections, discuss some of the existing routing protocols. DESTINATION-SEQUENCED DISTANCE-VECTOR ROUTING (DSDV)
The Destination 'Sequenced Distance-Vector Routing (DSDV) is based on the idea of Bellman-Ford Routing mechanism with certain improvements. Every mobile node in the network maintains a routing table. This routing table contains all of the possible destinations within the network, and the number of hops to each destination are stored. In this table, each entry is marked with a sequence number assigned by the destination node. The sequence numbers is useful for mobile nodes to identify old routes from new routes, so sequence number is also useful to avoid the formation of routing loops. To maintain the table consistency, routing table updates are periodically transmitted throughout the network. The stations transmit their routing tables to their immediate neighbors periodically. A station also transmit its routing table, if there is any significant change has occurred which is done with last update sent. Here, the update is both time-driven and event-driven. The routing table update can be sent in two ways- a 'full dump' or an incremental update. In full dump mode, a packet sends the full routing table to its neighbors and can require multiple network protocol data units (NPDUs). When the network is relatively stable, incremental updates are sent to avoid extra traffic and full dump are relatively infrequent. In incremental update mode, packets are used to relay only that information which has changed since the last full dump [5]. THE WIRELESS ROUTING PROTOCOL (WRP)
The Wireless Routing Protocol (WRP) is a table-driven distance vector routing protocol. Each node in the networks maintains the following four tables
' Distance table
' Routing table
' Link-Cost table and
' Message Retransmission list (MRL)
The Distance table of a node p contains the distance of each destination node q via each neighbor r of p. The routing table of node p contains the distance of each destination node q from node p, it also contains the information about the predecessor and the successor of node p on this path. This Routing table also contains the information to identify if the entry is a simple path, a loop or invalid via a tag field. The information about predecessor and successor which is stored in the routing table, is beneficial in detecting loops and avoiding counting-to-infinity problems. The Link-Cost table contains cost of link to each neighbor of the node and the number of timeouts since an error-free message was received from the neighbor. Each entry of the MRL contains the sequence number of the updated message, a retransmission counter, an acknowledgement required flag vector with one entry per neighbor, and a list of updates sent in the updated messages [5]. CLUSTER SWITCH GATEWAY ROUTING PROTOCOL (CSGRP)
Cluster Switch Gateway Routing Protocol (CSGR) uses as basis the DSDV Routing algorithm. CSGR protocol differs from the DSDV protocol in the type of addressing and network organization scheme employed. Instead of a flat network, CGSR is a clustered multi- hop mobile wireless network with several heuristic schemes. The mobile nodes are grouped into clusters and a cluster-head is selected. This cluster head controlling a group of ad hoc nodes, a framework for code separation (among clusters), channel access, routing, and bandwidth allocation can be achieved. For the selection of head node, a cluster head selection
algorithm within the cluster. The disadvantage of having a cluster head scheme is that cluster head changes frequently, so it can adversely affect routing protocol performance since nodes are busy in cluster head selection rather than packet replaying. To avoid this scenario, Invoking cluster head reselection every time the cluster membership changes, a Least Cluster

Figure 1.3: CGSR: routing from node 1 to node 8 [5].

Change (LCC) clustering algorithm is introduced. Using LCC, cluster heads change only when two heads come into contact or when a node moves out of contact of all cluster heads. CGSR uses DSDV as the underlying routing scheme, and CGSR has much of the same overhead as DSDV. It modifies DSDV by using hierarchical cluster routing approach to route traffic from source to destination. Gateway nodes are those nodes that are within communication range of two or more cluster heads. A packet sent by a node is first routed to its cluster head, and then the packet is routed from the cluster head to a gateway to another cluster head, and so on until the cluster head of the destination node is reached. The packet is then transmitted to the destination. This routing scheme is shown in figure 1.3. Using this method, each node must keep a 'cluster member table' where it stores the destination cluster head for each mobile node in the network. These cluster member tables are broadcast by each node periodically using the DSDV algorithm. Nodes update their cluster member tables on reception of such a table from a neighbor [5].
An approach that is different from Table-Driven Routing is Source-Initiated On-Demand Routing (SIODR) [3]. This type of routing creates routes only when desired by the source node. When a node requires a route to a destination, it initiates a route discovery process within a network. This process is completed once a route is found or all possible route permutations have been examined. Once a route has been discovered and established, it is maintained by some form of route maintenance procedure until either the destination becomes inaccessible along every path from the source or the route is no longer desired. SIODR can be classified further as Adhoc On-Demand Distance Vector Routing (AODV), Dynamic Source Routing (DSR), Temporally Ordered Routing Algorithm (TORA), Signal Stability Routing (SSR), Location-Aided Routing (LAR), Power Aware Routing (PAR), Zone Routing Protocol (ZRP), and Relative Distance Microdiversity Routing (RDMAR) [4]. In the following sections, discuss some of the existing routing protocols. AD HOC ON-DEMAND DISTANCE VECTOR ROUTING (AODV)
Ad hoc on-demand Distance Vector Routing (AODV) is an improvement of DSDV routing protocol. AODV routing protocol minimizes the number of required broadcasts by creating routes on-demand basis as opposed to DSDV that maintains the list of all the routes.
To find a path to a destination, the source broadcast a route request packet. After receiving route request packet, the neighbors also broadcast the packet to their neighbors till it reaches an intermediate node that has a recent route information about the destination. The propagation of Route Request Packet (RREQ) is shown in figure 1.4.
Figure 1.4: Propagation of Route Request Packet.

A node discard route packet if it is already received by a node. Route request packet has a sequence number to ensure that the routes are loop free and to make sure that if intermediate nodes reply to route requests, they reply with the latest information only.
When a route request packet is forwarded by a node to its neighbors, it also records in its tables the node from which the first copy of the request came. The stored information is used to construct the reverse path for the Route Reply Packet (RREP). AODV routing protocol uses only symmetric links because the route reply packet follows the reverse path of route request packet. As soon as route reply packet traverses towards to the source, the nodes along the path enter the forward route into their tables. The path taken by the Route Reply Packet (RREP) is shown by the following figure 1.5.

Figure 1.5: Path Taken by Route Reply Packet.

If the source moves then it is able to reinitiate the route discovery protocol to find a new route to the destination. If one of the intermediate nodes move then the neighbors of moved nodes realizes that the link failure is done and sends a link failure notification to its upstream neighbors and so on till it reaches the source upon which the source can reinitiate route discovery if needed [5]. DYNAMIC SOURCE ROUTING (DSR)
The Dynamic Source Routing Protocol is based on the concept of source-routed on-demand routing protocol. Mobile nodes are required to maintain route caches containing the source routes of which the mobile is aware. The nodes update entries in the route cache as continually and when it learns about new routes.
DSR protocol have two major phases: route discovery and route maintenance. When a mobile node sends a packet to the destination, it first consults its route cache to determine whether it already has a route to the destination. If it has a route to the destination, it will use this route to send the packets. If there is no such existing route, it initiates route discovery by broadcasting a route request packet. This route request contains the destination address, source address and a unique identification number. Each node receiving the packet checks whether it knows of a route to the destination. If such route does not exist then it adds its own address to the route record of the packet and then forwards the packet to its neighbors. To limit the number of route requests packet propagated on the neighbors of a node, a mobile only forwards the route request if the request has not yet been seen by the mobile and if the mobile's address does not already appear in the route record. Building record route during route discovery is shown by following figure 1.6.

Figure 1.6: Building Record Route during Route Discovery.

A route reply is generated when either the destination or an intermediate node with current information about the destination receives the route request packet. A route request packet reaching such a node already contains, in its route record, the sequence of hops taken from the source to this node. To return the route reply, the responding node must have a route to the source. The reverse of route record can be used if symmetric links are supported. If the symmetric links are not supported, so the node can initiate route discovery to source and the route reply on this new route request by piggybacking. Propagation of Route Reply with the Route Record is shown by the following figure 1.7.
Figure 1.7: Propagation of Route Reply with Route Record.

Route maintenance is done through with route error packets and acknowledgements. When the data link layer encounters a fatal transmission problem, then route error packets are generated at a node. The hop in error is removed from the node's route cache and all routes containing the hop are truncated at that point when a route error packet is received. Acknowledge packets are used to verify the correct operation of the route links. This includes passive acknowledgements, where a mobile is able to hear the next hop forwarding the packet along the route [5]. TEMPORALLY ORDERED ROUTING ALGORITHM (TORA)
The Temporally Ordered Routing Algorithm (TORA) is highly adaptive, efficient, loop free, and scalable distributed routing algorithm based on the concept of link reversal. TORA is proposed for highly dynamic multihop mobile networking environment. The TORA routing protocol is based on the Light-weight Mobile Routing (LMR) [6] protocol. It is a source-initiated on-demand routing protocol. This protocol is used to find multiple routes from a source node to a destination node. The main feature of TORA is that the localization of control messages to a very small set of nodes near the occurrence of a topological change. To achieve this, the routing information about adjacent nodes is maintained by the nodes. This protocol performs three basic functions
' Route Creation
' Route Maintenance
' Route Erasure
Nodes uses a height metric to establish a directed acyclic graph (DAG) rooted at the destination, during the route creation and maintenance phases. Therefore links are assigned an upstream direction or downstream direction based on the relative height metric of neighboring nodes as shown in following figure 1.8.

Figure 1.8: Route Creation in TORA [5].
The procedure of establish a DAG is similar to the query/reply process proposed in (LMR). In times of node mobility the DAG route is broken, and it is necessary to maintain route to reestablish a DAG rooted at the same destination. Route maintenance is shown in following figure 1.9.

Figure 1.9: Route Maintenance in TORA [5].

Each node has five tuple associated with it
' Logical time of a link failure
' The unique ID of the node that defined the new reference level
' A reflection indicator bit
' A propagation ordering parameter
' The unique ID of the node
The first three tuples represent the reference level. A new reference level is defined each time a node loses its downstream link due to a link failure. To erase invalid routes, TORA's route erasure phase essentially involves flooding a broadcast clear packet (CLR) throughout the network [5]. ASSOCIATIVITY-BASED ROUTING PROTOCOL (ABR)
Associativity-Based Routing (ABR) is source initiated routing protocol. To determine routes to the required destinations, ABR also uses a query-reply technique. Route selection in ABR is primarily based on stability. For selection of stable route, each node maintains an associativity tick with their neighbors and the links with higher associativity tick are selected in preference to the once with lower associativity tick. ABR protocol is loop free, deadlock free and also free from packet duplicates and defines a new routing metric for ad hoc mobile networks. This metric is known as the degree of association stability. The degree of association stability of mobile nodes is responsible for route selection in ABR. Each node generates periodically a beacon to justify its existence. This beacon causes their associativity tables to be updated when received by neighboring nodes. The association tick of the current node with respect to the beaconing node is incremented, for each beacon received. Association stability defines connection stability of one node to another node over time and space. A low state of node mobility is indicated by a high degree of association stability while a high state of node mobility is indicated by a low degree of association stability. When the neighbors of a node or the node itself move out of proximity then associativity ticks are reset. There are three fundamental objective of ABR to find longer-lived routes for ad hoc mobile networks. The objectives are
' Route Discovery
' Route Reconstruction (RRC)
' Route Deletion
The route discovery phase is done by a broadcast query and await-reply (BQ-REPLY) cycle. RRC is used for partial route discovery, invalid route ensure, valid route updates, and new route discovery, depending on which node or nodes along the route move. Route delete broadcast is initiated by source node when a discovered route is no longer needed [5-6]. Route maintenance for source and destination movement in ABR is shown by following figure 1.10.

Figure 1.10: Route maintenance for source and destination movement in ABR [5].
Battery power is a rare resource in wireless ad hoc and it often affects the all communication related activities in network.
Mobile computing is evolving rapidly with advances in wireless communications and wireless networking protocols. Despite the fact that devices are getting smaller and more efficient, advances in battery technology have not yet reached the stage where a mobile computer can operate for days without recharging. While research is on-going to build long-lasting batteries, sometimes we wonder if there is an electrochemical limit [7]. Device manufacturers have always been striving for lower power consumption in their products so that these devices are efficient to operate. A mobile computer is composed of many different devices such as hard disk drives, LCD/LED displays, CD/DVD ROMs, etc. Each of these devices has its own power requirements, operational characteristics, and usage patterns, which make power management in the overall system complicated. The answer to more comprehensive power management (PM) is advanced power management (APM) which was followed recently by operating system power management (OSPM) and advanced configuration power interface (ACPI).
In APM, one or more layers of software are present to support PM in computers with power-manageable hardware. APM's objective is to control the power usage of a system based on the system's activity. Power is reduced gradually as more system resources remain unused until the system suspended [7].
On the other hand, ACPI defines new ways of power control. It enables an operating system to implement system-directed PM. The ACPI hardware interface is a standardized way to integrate PM through a portable system's hardware, OS, and application software. The ACPI gives the operating system direct control over the PM and plug-and-play functions of a computer [7].
There is no fixed infrastructure in wireless ad hoc network. Each node has its own limited power sources. Therefore, the energy conservation schemes are important issues for researchers. There are many existing schemes for conserving power in wireless ad hoc networks. These schemes are used to reduce the power used by the radio transceiver. Thus, there can be following techniques to optimize the power consumption [8]
' Power Conservation via Controlling Transmission Power
' Power Conservation via using Power Management Technique
' Power Conservation via using Minimized Power Aware Routing Protocol
' Power Conserving at Mobile Nodes



Development of the efficient routing protocol with optimal energy consumption is the important issue for wireless adhoc network. It is very necessary to provide efficient route from source node to destination node to deliver packet or data in wireless adhoc network. Here battery power of a node is a prime concern that should be used efficiently to provide a better and a long time communication with other nodes in a network. Thus, it is an important issue to manage energy efficiently in wireless ad hoc networks [4].
The life of a node can be increased by using efficient battery management, transmission power management, and system power management. There are three major energy management schemes as shown in Figure 2.1. The energy management approaches can be classified as Battery Management Schemes, Transmission Power Management Schemes, and System Power Management Schemes. Battery management is concerned with how we select battery technologies, optimal battery capacity, and proper scheduling of batteries to increase capacity. By improving the capacity of battery, we can increase life time of a node. Transmission power management techniques are used to find and manage optimal transmission range for the nodes in wireless ad hoc network [9]. System power management techniques are used to minimize the power which is used by hardware of a node.
Battery life period can be increased by adjusting the transmission power of nodes, proper end to end packet delivery. There are some reasons for energy management in wireless adhoc networks as Limited Energy resource for nodes; it is not easy to replace batteries; Lack of a proper Coordination between nodes; Selection of the optimal transmission power and Proper Channel Utilization [9].

Figure 2.1: Classification of energy management schemes
At network layer concern, the prime issue to develop and design an efficient routing protocol. After developing an efficient routing algorithm, that routing algorithm should be able to increase the network life time by selecting an optimal relay node. The prime concern of this work is to develop an efficient routing protocol for wireless adhoc networks and as well as this routing protocol will take care of energy consumed by the nodes.
The power is consumed by nodes at network layer by mainly two operations that are communication and computation. In communication, power is consumed whenever a node is active during transmission or reception of packets. Power is also consumed whenever a node in listening mode but it is not participating actively for that communication. If a node is waiting for packets that is delivered by a desired sender, in this particular case the battery is also consumed by that node continuously even when it is on waiting mode. In computation mode, power is consumed during routing calculations and power adjustments [10].
It is very difficult to develop and design a new routing protocol that can efficiently manage the utilization of energy of nodes to optimize the network life time.
All energy efficient techniques have the same goal that is how to maximize network lifetime but there is no parameter to define network lifetime. The objective of this work is to develop a new routing algorithm which provides an efficient way to manage energy of the nodes in wireless ad hoc networks.
The primary objectives of the work undertaken are:-
' Minimizing the energy consumed per packet
' Maximizing the time before the network is partitioned
' Minimizing the variance in node power levels
' Minimizing the cost per packet
' Minimizing the maximum node cost
The protocol selects routes that have a longer overall battery life. In this research work, an energy optimized AODV (AOVDEO) routing protocol is proposed which performs routing based on the combination of least hops and minimum remaining energy to find shortest path from source to destination. After that this protocol evaluates energy for hop to hop data packet transmission.



In the literature survey, various papers are reviewed. With the help of these papers, an idea is taken for this research work, and the review summary of these papers are as follows-
S Jayashree et.al [9], this paper describes the taxonomy of various energy management schemes for wireless adhoc networks and a comprehensive summary of a scheme under each classification. It's also points out the future research perspectives in energy management for these networks. They also point out various energy management schemes as Battery Management Schemes, Transmission Power Management Schemes, and System Power Management Schemes. Battery management is concerned with how we select battery technologies, optimal battery capacity, and proper scheduling the batteries to increase capacity. By improving the capacity of battery, we can increase life time of a node. Transmission power management techniques are used to find and manage optimal transmission range for the nodes in wireless adhoc network. System power management techniques are used to minimize the power which is used by hardware of a node.
Vinay Rishiwal et.al [10], in this paper, an algorithm is proposed which maximizes the network lifetime by minimizing the power consumption during the source to destination route establishment. This algorithm's performance is better than AODV and DSR in terms of various energy related parameters like Total Energy Consumption, Average Energy Left Per Alive Node, Node Termination Rate, and Network Lifetime for different network scenario. This algorithm takes special care to transfer both real time and non real traffic by providing energy efficient and less congested path between a source and destination pair. This algorithm basically focuses on three parameters as Accumulated Energy of a path, Status of Battery Lifetime, Type of Data to be transfer such as Non Real Time (NRT) and Real Time (RT).
Radhika D Joshi et.al [11], in this paper, an algorithm is proposed that is an efficient modified AODV (AODVM) routing protocol which performs routing based on the combination of least hops and minimum remaining energy. In this protocol, first, a route is selected on the behalf of minimum hop count between source and destination (i.e. AODV routing protocol). After that a route is selected with largest minimum residual energy (i.e. AODVEA routing protocol). And the last, a route is selected with the largest minimum residual energy and less hop count i.e. with the longest network lifetime (i.e. proposed AODVM routing algorithm).
There are many papers which are reviewed. This is one of the papers from where an idea is taken to design and develop an algorithm [11]. This proposed algorithm will enhance the network lifetime and minimizes the energy consumptions. For this, several papers are studied and these different papers to accumulate this idea by the help of which this research work can move further. The details of different papers from which this idea is accumulated, are described below-
Rohit Khot et.al [12], this paper points out the problem of unicasting in wireless adhoc networks. Unicasting is the problem of finding a route between a source to a destination and forwarding the message from the source to the destination. They proposed Wireless Communication Model-in this model it's not just model transmission and interference range but it also model physical carries sensing. Physical carrier sensing is used by the Medium Access Control (MAC) layer to check whether the wireless medium is currently busy. In Routing Model-this paper assume that the node labels for the source and the destination are distinct. The other nodes need labels that are only locally distinct. These algorithms do not also require that nodes know their co-ordinate position via GPS.
Qing Zhao et.al [13], this paper presents a hybrid networking strategy for large scale energy constrained ad hoc networks. It referred this hybrid approach as EAGER (Energy-Aware Geo-location aided Routing), this protocol use both routing approaches proactive and reactive routing strategies for energy efficiency. The basic idea of EAGER is to partition the network into equal sized cells. Routes within cell are maintained proactively while across cells route are established reactively.
Krishan Kumar et.al [14], this paper focuses on various energy consumption issues for wireless adhoc network. It also focuses how the energy can be used efficiently. It's proposed various factors by which we can reduce energy consumption and the factors are- Energy saving by route discovery, Energy saving by transmission power, Energy saving by transmission range and Energy saving by energy management model.
Anshu Chaturvedi et.al [15], this paper presents an algorithmic approach to the problem of routing with minimum energy consumption in the ad hoc network. This paper has proposed an energy optimal path algorithm used for routing in static adhoc networks using greedy approach of algorithm design. This algorithm will result in a path which will be optimal in terms of energy as well as the distance. It will be energy optimized shortest path or route. Through this algorithm they discovered a path which forwards the packet with more reliability, less energy consumption, balanced delay, and balanced overhead and increased throughput. So the connectivity and the network lifetime can be improved, and that is verified simulation by them.
Sachin Sharma et.al [16], this paper presents Energy Aware Greedy Routing (EAGR) scheme for wireless ad hoc networks. In this scheme, the cost metric of a node depends on the following parameters of a neighboring node: (1) Distance from the destination, (2) Fraction of energy consumed, and (3) Rate of energy consumption. When a node has the least cost metric, the packet is forwarded to that node. It evaluates the performance of EAGR in static wireless ad hoc network by replacing the greedy routing of Greedy Perimeter Stateless Routing (GPSR) protocol with EAGR.
Sunil Taneja et.al [17], this paper proposed a scheme that takes consideration the power awareness during the route selection. This scheme observes power status of each and every node in the topology and further ensures the fast selection of routes with minimal efforts and faster recovery. This scheme is incorporated with AODV protocol. In this proposed algorithm, it assumes that the nodes which are not participating in route for packet delivery should go to sleep mode from the start. After that source node broadcasts an active request to the destination (this request is same as RREQ as used in AODV) and check the reply phase and set active path as a connection establishment and finally send the packet from source to destination.
Saswati Sarkar et.al [18], this paper focuses to extend the lifetime of a battery powered node in wireless context. The lifetime of a battery depends on the transmission power requirements and the manner of discharge. This paper present a framework for computing the optimal discharge strategy which maximizes the lifetime of a node by exploiting the battery characteristics and adapting to the varying power requirements for wireless operations. The complexity of the optimal computation is linear in the number of system states. Since the number of states can be large, the optimal strategy can only be computed offline and executed via a table lookup. This paper presents a simple discharge strategy which can be executed online without any table lookup and attains near maximum lifetime. This paper provides an optimal battery discharge policy, for maximizing the lifetime of the power limited wireless terminals.
Vikas Kawadia et.al [19], this paper consider the problem of power control when nodes are non-homogeneously dispersed in space. In such situations, one seeks to employ per packet power control depending on the source and destination of the packet. This gives rise to a joint problem which involves not only power control but also clustering. It provides three solutions for joint clustering and power control.

The first protocol is CLUSTERPOW. The objective of this protocol is to increase the network capacity by increasing spatial reuse. This paper provide a simple and modular architecture to implement CLUSTERPOW at the network layer.
The second protocol is Tunnelled CLUSTERPOW. This protocol allows a finer optimization by using encapsulation, but there is not an efficient way to implement it.
The last protocol is MINPOW. The basic idea is not new, it provides an optimal routing solution with respect to the total power consumed in communication. This paper includes a clean implementation of MINPOW at the network layer without any physical layer support.
It establish that all three protocols ensure that packets ultimately reach their intended destinations. It also provide a software architectural framework for their implementation as a network layer protocol. The architecture works with any routing protocol, and can also be used to implement other power control schemes.
Myung Jong Lee et.al [20], over the past decade, wireless multihop ad hoc networks have received a tremendous amount of research focus, at the core of which lies the design problem for efficient routing algorithm to meet various scenarios and applications. This paper introduces a new routing protocol design concept- the component approach. It examines existing routing protocols and break them down into smaller building blocks, namely routing components. The component analysis and classification results show that most routing protocols can be functionally decomposed into several basic routing components. This fact indicates that it is feasible to design a routing that is a component-based routing (CBR) protocol. With a different realization for each basic routing component, it is expected that the routing behavior of CBR can be tailored to different application profiles and time 'varying environment parameters at a reasonable cost.
Rong Zheng et.al [21], battery power is an important resource in ad hoc networks. It has been observed that in ad hoc networks, energy consumption does not reflect the communication activities in the network. Many existing energy conservation protocols based on electing a routing backbone for global connectivity are oblivious to traffic characteristics. This paper propose an extensible on-demand power management framework for ad hoc networks that adapts to traffic load. Soft-state timers are maintained by nodes that determine power management transitions. These timers are set and refreshed on-demand by monitoring routing control messages and data transmission. Nodes that are not involved in data delivery may go to sleep as supported by the MAC protocol. This soft state is aggregated across multiple flows and its maintenance requires no additional out-of-band messages. It implements a prototype framework in the NS2 simulator that uses the IEEE 802.11 MAC protocol. Simulation studies using our scheme with the Dynamic Source Routing protocol show a reduction in energy consumption near 50% when compared to a network without power management under both long-lived CBR traffic and on-off traffic loads, with comparable throughput and latency. Preliminary results also show that it outperforms existing routing backbone election approaches.
C.-K. Toh [22], most ad hoc mobile devices today operate on batteries. Hence, power consumption becomes an important issue. To maximize the lifetime of ad hoc mobile networks, the power consumption rate of each node must be evenly distributed, and the overall transmission power for each connection request must be minimized. These two objectives cannot be satisfied simultaneously by employing routing algorithms proposed in previous work. This paper presents a new power-aware routing protocol to satisfy these two constraints simultaneously, it also compare the performance of different types of power-related routing algorithms via simulation. Simulation results confirm the need to strike a balance in attaining service availability performance of the whole network vs. the lifetime of ad hoc mobile devices.
Javad Vazifehdan et.al [27], energy-aware routing is an effective way to prolong the lifetime of nodes with scarce battery power in ad hoc networks. The proposed energy-aware routing schemes so far do not consider the energy supply of nodes in route selection. They only consider the residual battery capacity of nodes. This paper proposes energy aware routing algorithms for ad hoc networks with both battery-powered and mains powered nodes. The proposed algorithms direct the traffic load to mains-powered nodes to avoid using battery-powered nodes as relay. By tuning some tunable coefficients, these algorithms can provide a trade-off between the operational lifetime of the network and the hop count of the selected routes. It compares the performance of the proposed algorithms with other algorithms which do not differentiate explicitly between mains-powered and battery-powered nodes. It shows that when most of the nodes in the network are mains-powered, the use of only the type of power supply of nodes in route selection results in a higher network lifetime compared to using the residual battery capacity of nodes. This implies that in such cases, the routing overhead can be reduced, since there is no need to repeatedly propagate the residual battery capacity of nodes (as needed in so-far proposed energy-aware routing algorithms), while even the network lifetime increases.
Chih-Cheng Tseng et.al [28], optimizing the transmission ranges between nodes and balancing the number of nodes among clusters are two feasible approaches to conserve the limited battery power in exchanging messages when designing power-efficient (or green) clustered wireless ad hoc networks. To achieve this objective, this paper first employ the concept of Relative Neighborhood Graph (RNG) to obtain a power-efficient logical network topology in which the transmission ranges between nodes are adjusted to the optimal. Then, based on the obtained RNG-based logical network topology, it present a green clustering algorithm to organize the wireless ad hoc network into a clustered architecture in which the number of nodes among clusters is balanced. Simulation results confirm that the presented approaches not only optimize the transmission ranges between nodes but also balance the number of nodes among clusters. Thus, the organized clustered wireless ad hoc network is regarded as power-efficient (or green).
Amit Chaturvedi et.al [32], Ad-hoc networks are becoming increasingly popular due to their wide range of uses. Mobile ad-hoc network have Nodes for at no cost to move and arrange them in random order. Ad-hoc networks are suitable for make use of in situation where an infrastructure would not unavailable or to deploy one is not cost effective. In ad- hoc networks MAC protocols are responsible for coordinating access from active nodes. Different MAC protocols with various objectives have been projected for wireless ad hoc networks. Almost of the wired networks based on the symmetric links, which are always unchanging. But this is not a crate with ad-hoc networks as the nodes are movable and continuously varying its position within network. Maximize the network life span, is regular purpose of ad hoc network, since ad hoc network nodes are understood to be dead when they are without of battery. Another main objective is increasing the capacity of the network. However this paper have shown that some schemes degrade the network throughput as well as bring unfairness in the network in order to save energy and to increase the network throughput as compared to the standard protocol. The proposed methods give a very high energy saving and better throughput which increases the battery life of the ad hoc nodes making the system cost effective. Also the proposed schemes bring fairness in the pair wise network throughput.



The nodes in wireless ad hoc networks are energy specific. If a node wants to communicate then there can be a number of nodes as intermediate nodes between source to destination node. So energy is crucial issue for wireless ad hoc network's node. The life of a node can be increased by using efficient battery management, transmission power management, and system power management. Battery life period can be increased by adjusting the transmission power of nodes, proper end to end packet delivery. There are some reasons for energy management in wireless ad hoc networks as Limited Energy resource for nodes; it is not easy to replace batteries; Lack of a proper Coordination between nodes; Selection of the optimal transmission power and Proper Channel Utilization. The power is consumed by nodes at network layer by mainly two operations that are communication and computation. In communication power is consumed whenever a node is active during transmission or reception of packets. Power is also consumed whenever a node in listening mode but it is not participating actively for that communication. If a node is waiting for packets that is delivered by a desired sender, in this particular case the battery is also consumed by that node continuously even when it is on waiting mode. In computation mode, power is consumed during routing calculations and power adjustments.
To enhance the lifetime of the network, one possible solution is-the efficient utilization of wireless ad hoc nodes. AODV routing protocol does not consider the residual energy of nodes ate the routing setup, it considers only routing hop count as a distance metric, unbalanced node energy consumptions occurs.
In AODVEA [11], this routing is based on the metric of minimum remaining energy. First such nodes are marked that have minimum remaining energy in the route and then route having maximum of minimum remaining energy is selected. For this, Minimum Remaining Energy (Min-RE) field is added to the RREQ and RREP packet format. Min-RE field gives the nodes with minimum remaining energy in the route. Other parameters are as same as used in AODV route request.
After receiving first valid route reply packet, the source node starts communication. Once source S receives the next route reply, it runs following algorithm [11]
1. Send a RREQ (Route Request)
2. Get various routes available to destination.
3. Compare parameters of routes with respect to remaining energy level and least count.
4. Then the appropriate route for destination is selected
In AODV Energy Aware (AODVEA), routing is based only on the metric of minimum energy. The node having minimum remaining energy in the route is identified first and route having maximum of minimum remaining energy is selected. For this, Energy by hops field is added to Min-RE field in both RREQ and RREP packet format. Other parameters are same as used in AODVEA route request [11].
AODVM protocol performs a route discovery process same as AODV protocol. The basic difference is that the route selection is determine by considering residual energy of nodes on the path and hop count. To implement such functions, a new field, called Min-RE field, is added to the RREQ packet. When a source node broadcasts a new RREQ message for a route discovery process, the Min-RE field is set to a default value of -1. Source node floods a RREQ packet to the network to find a route to a destination. When neighbors receive the RREQ packet, they update the Min-RE value and they further broadcast the packet to its neighbors until the packet arrives at a destination node. If the intermediate nodes receive a RREQ message, they increase the hop count by one and replace the value of the Min-RE field with the minimum energy value of the route. In other words, Min-RE is the energy value of the node if Min-RE is greater than its own energy value, otherwise Min-RE is unchanged. If the destination node receives the first RREQ packet, it triggers the data collection timer and receives all RREQ packet forwarded through other routes until time expires. After collecting all route information, it determines an optimal path and sends a RREP packet to the source node by unicasting. After receiving RREP packet, a route is establish and data transfer gets started between source to the destination. Such route processes are performed periodically. The optimum route is determined by using the value of ?? described as
?? = (Min-RE)/ Hop Count
After receiving all route information, the destination node calculates the value of ?? and choose a route that has the largest value of ??. Here Min-RE is the minimum residual energy on the route and No. of Hops is the hop count of the route between source and destination [11].
Existing system provides the efficient utilization of energy of wireless ad hoc nodes. But there is an enhancement is possible, this was the motivation for this research work of developing the new routing algorithm that will enhance the network lifetime and also optimize the power consumption when a route is established between source to a destination node for data transmission. In this research work, a new energy efficient algorithm is proposed.
The proposed algorithm AODVEO (AODV Energy Optimized) has four step. To understand the operations of the proposed algorithm, it consider four different routing protocols for operational comparison
Algorithm: AODVEO
Step 1: Choose a route with minimum hop count between source and destination (AODV Routing Protocol)
Step 2: Choose a route with largest minimum residual energy (AODVEA Routing Protocol)
Step 3: Choose a route with the large minimum residual energy and less hop count (AODVM Routing Protocol)
Step 4: Choose a hop to hop route with required minimum residual energy (AODVEO Routing Protocol)





Energy efficiency is one of the main problems in a mobile ad hoc network, especially designing a routing protocol. The proposed work aims at discovering an efficient power aware routing scheme in MANETs which can support both real and non-real time traffic. Simulation result shows that the proposed scheme PAR is outperforms in terms of different energy related parameters over AODV and DSR even in high mobility scenarios. At the time route selection PAR take care of crucial things like traffic level on the path, battery status of the path, and type of request from user side. With these factors in consideration PAR always select less congested and more stable route for data delivery.
In this paper, the brief survey of ad-hoc routing protocols is provided. From them AODV is chosen for further enhancement. The importance of energy conservation in ad hoc routing is explained. Then the routing is done based on the metric of the remaining energy in energy aware AODV. The modified AODV performs routing based on both hop count and minimum
remaining energy. From the simulation performed for various scenarios, the following conclusions can be made.
Network Lifetime:
Average Delay:
Energy Consumption:



This research work can be extended for other parameters such as packet delivery ratio, Average Energy Left per Alive Node, Node Termination Rate, the latency of the data transfer but it results in a significant power saving and long lasting routes. The process of checking the proposed scheme is on for more sparse mediums and real life scenarios and also for other metrics like Path optimality, Link layer overhead, total energy consumed etc. This approach of routing using a combination of Hop count and remaining energy will give much better performance for longer simulation period. Simulations are required to be done for other parameters such as link capacity combined with the route selection logic so that overall QoS of wireless network can be improved.



[1] Sushma D. Ghode, and K. K. Bhoyar, 'A Survey on Energy Efficient Routing Algorithms for Ad-Hoc Network' in International Journal of Computer Applications, Volume 67' No. 20, April 2013, pp. 44-50.
[2] C.K. Toh, 'Ad Hoc Wireless Networks', Adhoc Mobile Wireless Networks: Protocol and Systems, Tenth Impression, Noida, India: Pearson Education, Inc. and Dorling Kindersley Publishing, Inc., 2010, chapter 3, sec. 3.1, pp. 27.
[3] C.K. Toh, 'Overview of Ad Hoc Routing Protocols', Adhoc Mobile Wireless Networks: Protocol and Systems, Tenth Impression, Noida, India: Pearson Education, Inc. and Dorling Kindersley Publishing, Inc., 2010, chapter 5, sec. 5.1-5.14, pp. 57-75.
[4] C.K. Toh, 'Energy Conservation: Power Life Issues', Adhoc Mobile Wireless Networks: Protocol and Systems, Tenth Impression, Noida, India: Pearson Education, Inc. and Dorling Kindersley Publishing, Inc., 2010, chapter 9, sec. 9.1-9.2, pp. 143-144.
[5] S. Jayashree, and C. Siva Ram Murthy, 'A Taxonomy of Energy Management Protocols for Ad Hoc Wireless Networks' in Communications Magazine, IEEE, Volume 45-issue 04, April 2007, pp 104-110.
[6] Vinay Rishiwal, Manu Yadav, S. Verma, and S. K. Bajapai, 'Power Aware Routing in Ad Hoc Wireless Networks' in JC & T, Volume 09' No. 2, October 2009.
[7] Radhika D. Joshi and Priti P. Rege, 'Energy Aware Routing in Adhoc Networks', Sixth International Conference on Circuits, Systems, Electronics, Control and Signal Processing (WSEAS), December 2007, pp 469-475.
[8] Rohit Khot, Ravikant Poola, Kishore Kothapalli, and Khanna Srinathan, 'Self-Stabilizing Routing Algorithms for Wireless Ad-Hoc Networks', Bangalore, India, ICDCIT, Springer, 2007, pp 54-56.
[9] Qing Zhao, and Lang Tong, 'Energy-Efficient Adaptive Routing For Ad Hoc Networks with Time-Varying Heterogeneous Traffic', in ICASSP, IEEE International Conference, Volume 05, 2005, pp v/801-v/804.
[10] Krishan Kumar, and Y.K. Jain, 'Literature Survey on Energy Consumption Control for Wireless Mobile Ad-hoc Network', IJECS, Volume 02, August 2013, pp 2645-2648.
[11] Anshu Chaturvedi, D.N. Goswami, and Tripti Sharma, 'Energy Optimal Path Algorithm for Routing in Static Adhoc Network Using Greedy Approach', IJCA, Volume 48-N0. 24, June 2012, pp 23-28.
[12] Sachin Sharma, H.M. Gupta, and S. Dharmaraja, 'EAGR: Energy Aware Greedy Routing Scheme for Wireless Ad hoc Networks', SPECTS, IEEE Conference, June 2008, pp 122-129.
[13] Sunil Taneja, Ashwani Kush, Amandeep Makkar, and Bharat Bhushan, 'Power Management in Mobile Adhoc Network', International Transaction Journal of Engineering, Management, & Applied Science & Technologies, Volume 02-No. 2, 2011, pp 215-225.

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