Maximizing the Battery Life Time of the Wireless Ad- Hoc Network: An Overview

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1 Maximizing the Battery Life Time of the Wireless Ad- Hoc Network: An Overview Ashish Kumar Mrs. Simer Kapoor Mrs. Mukesh kumari PG student PDM Engineering Asst. Professor in PDM Asst. Professor in RPS College Bahadurgarh (Haryana) College Bahadurgarh (Haryana) Engineering College Mohindergarh ABSTRACT The modern information society will continue to emerge, and demand for wireless communication services will grow. Future generation wireless networks are considered necessary for the support of emerging services with their increasing requirements. Future generation wireless networks are characterized by a distributed, dynamic, selforganizing architecture. A Wireless ad-hoc network is a temporary network set up by wireless mobile computers (or nodes) moving arbitrary in the places that have no network infrastructure. Since the nodes communicate with each other, they cooperate by forwarding data packets to other nodes in the network. Thus the nodes find a path to the destination node using routing protocols. However, due to security vulnerabilities of the routing protocols, wireless ad-hoc networks are unprotected to attacks of the malicious nodes. One of these attacks is the Black Hole Attack against network integrity absorbing all data packets in the network. Since the data packets do not reach the destination node on account of this attack, data loss will occur. There Our main contribution in this paper is to Maximize the battery Life time of ad-hoc network. Keywords Wireless Ad-hoc Network, Black Hole Attack, Simulation,Security, Intrusion Detection Systems. 1. INTRODUCTION "Ad Hoc" is actually a Latin phrase that means "for this purpose." It is often used to describe solutions that are developed on-the-fly for a specific purpose. In computer networking, an ad hoc network refers to a network connection established for a single session and does not require a router or a wireless base station. For example, if you need to transfer a file to your friend's laptop, you might create an ad hoc network between your computer and his laptop to transfer the file. This may be done using an Ethernet crossover cable, or the computers' wireless cards to communicate with each other. If you need to share files with more than one computer, you could set up a mutli-hop ad hoc network, which can transfer data over multiple nodes. Basically, an ad hoc network is a temporary network connection created for a specific purpose (such as transferring data from one computer to another). If the network is set up for a longer period of time, it is just a plain old local area network (LAN).Wireless ad-hoc networks are composed of autonomous nodes that are self-managed without any infrastructure. In this way, ad-hoc networks have a dynamic topology such that nodes can easily join or leave the network at any time. They have many potential applications, especially, in military and rescue areas such as connecting soldiers on the battlefield or establishing a new network in place of a network which collapsed after a disaster like an earthquake. Ad-hoc networks are suitable for areas Where it is not possible to set up a fixed infrastructure. Since the nodes communicate with each other without an infrastructure, they provide the connectivity by forwarding packets over themselves. To support this connectivity, nodes use some Routing protocols such as AODV (Ad-hoc On- Demand Distance Vector), DSR (Dynamic Source Routing) and DSDV (Destination-Sequenced Distance-Vector). Besides acting as a host, each node also acts as a router to discover a path and forward packets to the correct node in the network. As wireless ad-hoc networks lack an infrastructure, they are exposed to a lot of attacks. One of these attacks is the Black Hole attack. In the Black Hole attack, a malicious node absorbs all data packets in itself, similar to a hole which sucks in everything in. In this way, all packets in the network are dropped. A malicious node dropping all the traffic in the network makes use of the vulnerabilities of the route discovery packets of the on demand rotocols, such as AODV. In route discovery process of AODV protocol, intermediate nodes are responsible to find a fresh path to the destination, sending discovery packets to the neighbor nodes. Malicious nodes do not use 686 1

2 this process and instead, they immediately respond to the source node with false information as though it has fresh enough path to the destination. Therefore source node sends its data packets via the malicious node to the destination assuming it is a true path. Black Hole attack may occur due to a malicious node which is deliberately misbehaving, as well as a damaged node interface. In any case, nodes in the network will constantly try to find a route for the destination, which makes the node consume its battery in addition to losing packets. Fig.1 Ad-hoc Architecture Objectives of the AD-HOC Network: Each mobile host acts as a router Supports peer-to-peer communications Supports peer-to-remote communications WCDM A indoor base station HiperLA N/2 access point MT Reduced administrative cost Ease of deployment Speed of deployment. Decreased dependence on infrastructure Her PAN Bluet His PAN 1.1 Architecture of Ad-hoc network Wireless ad-hoc networks are composed of autonomous nodes that are self-managed without any infrastructure. In this way, ad-hoc networks have a dynamic topology such that nodes can easily join or leave the network at any time.they have many potential applications,especially,in military and rescue areas such as connecting soldiers on the battlefield or establishing a new network in place of a network which collapsed after a disaster like an earthquake. Ad-hoc networks are suitable for areas Where it is not possible to set up a fixed infrastructure. Since the nodes communicate with each other without an infrastructure, they provide the connectivity by forwarding packets over them selves. NC Figure 2. At an airport, where people can access local& wide-area networks, ad hoc Bluetooth connections are used to inter- connect carried devices, such as s, WCDMA mobile phones and notebook computers. For instance, a user might retrieve via a HiperLAN/2 interface to a notebook computer in a briefcase, but read messages and reply to them via his or her. 1.2 Types of Attack on Ad-hoc Network: 1. Gray hole attack NC 2. Black hole attack 2 687

3 3.Sleep Deprivation Torture Attack (Battery Exhaustion) Gray hole attacks is an active attack type, which lead to dropping of messages. Attacking node first agrees to forward packets and then fails to do so. Initially the node behaves correctly and replays true RREP messages to nodes that initiate RREQ message. This way, it takes over the sending packets. Afterwards, the node just drops the packets to launch a (DoS) denial of service attack. If neighboring nodes that try to send packets over Attacking nodes lose the connection to destination then they may want to discover a route again, broadcasting RREQ messages. Attacking node establishes a route Sending RREP messages. This process goes on until malicious node succeeds its aim (e.g. network resource consumption, battery consumption). This attack is known as routing misbehavior. Dropping packets is also one of the behaviors of failed or overloading nodes. One should not evaluate every dropping packet action as a selective existence, gray or black hole attack. Actually most routing protocols have no mechanism to detect whether data packets have been forwarded, DSR being the only exception. 2. Black Hole Attack: The difference of Black Hole Attacks compared to Gray Hole Attacks is that malicious nodes never send true control messages initially. To carry out a black hole attack, malicious node waits for neighboring nodes to send RREQ messages. When the malicious node receives an RREQ message, without checking its routing table, immediately sends a false RREP message giving a route to destination over itself, assigning a high sequence number to settle in the routing table of the victim node, before other nodes send a true one. Therefore requesting nodes assume that route discovery process is completed and ignore other RREP messages and begin to send packets over malicious node. Malicious node attacks all RREQ messages this way and takes over all routes. Therefore all packets are sent to a point when they are not forwarding anywhere. This is called a black hole akin to real meaning which swallows all objects and matter. To succeed a black hole attack, malicious node should be positioned at the center of the wireless network. If malicious node masquerades false RREP message as if it comes from another victim node instead of itself, all messages will be forwarded to the victim node. By doing this, victim node will have to process all incoming messages and is subjected to a sleep deprivation attack. Gray hole attacks against one or two nodes in the network to isolate them, where as black hole attack affects the whole network. Moreover, the malicious node that attempts gray hole attacks cannot be perceived easily since it does not send false messages. Behavior of failed or overloaded nodes may seem like selfish nodes attacks or gray hole attacks due to dropping of messages. But, since failed nodes cannot fabricate a new control message, they cannot form a black hole attack although they will drop the message later. 3. Sleep Deprivation Torture Attack (Battery Exhaustion) Many techniques are used to maximize the battery life and mobile nodes prefer to stay at the sleep mode, when they are not used. Sleep Deprivation Torture is one of the serious types of Denial of Service Attacks, which affects only nodes, especially handheld devices that have limited resources. In a period time, attacker can propagate some control messages through the network, in which other nodes are interested. Other nodes pass to the operation mode from the sleep mode and start processing these unnecessary packets until their batteries completely run out. Consider a group of wireless static nodes randomly distributed in a region as in Fig.3, where each node has a limited battery energy supply used mainly for the transmission of data. Assume that at each node some type of information is generated as it monitors the data such as sound or vibration in its vicinity using the sensor, and the information needs to be delivered to a set of gateway nodes. These wireless nodes are assumed to have the capability of packet forwarding, i.e., relaying an incoming packet to one of its neighboring nodes, and the transmitted energy level can be adjusted to a level appropriate for the receiver to be able to receive the data correctly if the receiver is within the transmission range. Upon or before a new arrival of information either generated at the node itself or forwarded from the other nodes, routing decision has to be made so that the node knows which of its neighboring nodes to forward its data to. Note that the routing decision and the transmission 3 688

4 energy level selection are intrinsically connected in this power controlled ad-hoc network since the power level will be adjusted depending on the location of the next hop node. An example scenario for this type of wireless ad-hoc network may include a wireless sensor network.fig. 3. Monitoring nodes Gateway Fig.3. A multi-hop wireless ad-hoc network is depicted where the nodes are randomly distributed and the information generated at the monitoring nodes is to be delivered to the gateway nodes. A multi-hop wireless ad-hoc network is depicted where the nodes are randomly distributed and the information generated at the monitoring nodes are to be delivered to the gateway nodes. acoustic, magnetic, or seismic information and send the information to its gateway node which has more processing power for further processing of the information or has larger transmission range for the delivery of the information to a possibly larger network for retrieval by a remote user. In [1], [6], we presented a simply implementable algorithm which guarantees strong connectivity and assumes limited node range. Shortest path algorithm is used in this strongly connected backbone network. However, the route may not be the minimum energy solution due to possible omission of the optimal links at the time of the backbone connection network calculation. The approach in those works was to minimize the total consumed energy to reach the destination, which minimizes the energy consumed per unit flow or packet. If all the traffic is routed though through the minimum energy path to the destination the nodes in that path will be drain-out of batteries quickly while other nodes, which perhaps will be more power hungry if traffic is forwarded through them, will remain intact. Instead of trying to minimize the consumed energy, the performance objective of maximizing the lifetime of the system which is equivalent to maximizing the time to network partition has been considered. the problem of maximizing the time to network partition was reported as NP-complete. In [3] we identified the maximum lifetime problem as a linear programming problem. Therefore, it is solvable in polynomial time. The work in [3] considered the single destination version of the problem, while here we extend the problem to the multicommodity case, where each commodity has its own set of destinations. In our study the topology of the network is static and the routing accounts to finding the traffic splits that balance optimally the energy consumption. Hence the results are applicable to networks which are either static, like the sensor networks we mentioned earlier, or whose topology changes slowly enough such that there is enough time for optimally balancing the traffic in the periods between successive topology changes. 4. ROUTING FOR THE MAXIMUM SYSTEM LIFETIME The wireless ad-hoc network in consideration is modeled as a directed graph G(N;A) where N is the set of all nodes and A is the set of all directed links (i; j) where i; j 2 N. Let Si be the set of all nodes that can be reached by node i with a certain power level in its dynamic range. We assume that link (i; j) exists if and only if j 2 Si. Let each node i have the initial battery energy Ei, and let Q i be the rate at which information is generated at node i belonging to commodity c 2 C, where C is the set of all commodities. Assume that the transmission energy required for node i to transmit an information unit to its neighboring node j is eij, and the rate at which information of commodity c is transmitted from node i to node j is called the flow q ij. Further, let Qi and qij be the aggregate flows of all commodities, i.e., 4 689

5 = fqijg is ) where under ISSN: Q i = cεc Q i (1) s.t. q ij 0, i N, j S i, c C, And + Q i q i = cεc q ij We are given, for each commodity c, a set of origin nodes O(c the information is generated, i.e., (2) O = {i Q i > 0, i ε N} (3) and a set of destination nodes D(c ) among which any node can be reached in order for the information transfer of commodity be considered done.the lifetime of node i a given flow q given T i (q) = Now, let us define the system lifetime under flow q as the length of time until the first battery drain-out among all nodes in N, which is the same as the minimum lifetime over all nodes, i.e., T sys (q) = min iεn T i (q) = min iεn (4) (5) Our goal is to find the flow that maximizes the system lifetime under the flow conservation condition. The problem can be written as follows: Maximize Tsys (q) = miniεn =, I N-D c, c C (6) 5. CONCLUSION In wireless ad-hoc networks, battery energy at network nodes is a very limited resource that needs to be utilized efficiently. One of the conventional routing objectives was to minimize the total consumed energy in reaching destination. However, the conventional approach may drain out the batteries of certain paths which may disable further information delivery even though there are many nodes with plenty of energy. Therefore, we formulated the routing problem with the objective of maximizing the system lifetime given the sets of origin and destination nodes and the information generation rates at the origin nodes, and proposed a class of flow augmentation algorithms and a flow redirection algorithm which balance the energy consumption rates among the nodes in proportion to their energy reserves. The proposed algorithm is local and amenable to distributed implementation and showed close to the optimal performance most of the time, significantly improving the system lifetime, that is, as much as 60% on the average over the conventional minimum transmitted energy routing. 6. REFERENCES [1] S. Murthy and J.J. Garcia-Luna-Aceves, An efficient routing protocol for wireless networks, ACM Mobile Networks and Applications Journal, Special Issue on Routing in Mobile Communication Networks, [2] Stephen G. Nash and Ariela Sofer, Linear and Nonlinear Programming, McGraw-Hill, [3] Vincent D. Park and M. Scott Corson, A highly distributed routing algorithm for mobile wireless networks, in Proc. IEEE INFOCOM 97, Kobe, Japan, [4] C. Perkins and P. Bhagwat, Highly dynamic destination-sequenced distance vector routing (DSDV) for mobile computers, in ACM SIGCOMM, Oct [5] Volkan Rodoplu and Teresa H. Meng, Minimum energy mobile wireless networks, in Proceedings of the 1998 IEEE International Conference on Communications, ICC 98, Atlanta, GA, June 1998, vol. 3, pp