RESA: Reliable Energy Efficient Self-Adaptive Routing Algorithm for WBAN

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1 RESA: Reliable Energy Efficient Self-Adaptive Routing Algorithm for WBAN Nisha Singh Sidhu 1, Timsi Arora 2 1 Research Scholar, 2 Asstt. Professor JCDM College of Engineering Sirsa, Haryana Abstract: Due to advancement in the telecommunication, wireless communication, wireless sensors, and other technologies a new field of research has been evolved and this area of research is termed as Wireless Body Area Networks. In WBAN miniaturized sensor nodes are implanted in the blood stream or on the human body. These sensor nodes are battery dependent, once the battery dies, node also dies. That s why minimum energy consumption with reliable data transmission is primary requirement in WBAN. To achieve minimum energy consumption there is a need of self-adaptive routing protocol. In this proposed work, a Reliable Energy Efficient self Adaptive (RESA) Algorithm has been proposed which considers hop count, link quality and energy consumption for reliable route discovery. Energy consumption is minimized in RESA by using the concept of piggyback scheme in which residual energy of different nodes are sent to their neighbors on demand and paths having nodes with low residual energy are skipped. RESA algorithm also uses a selfadaptive approach for even distribution of load in the communication network with minimum number of dead nodes and avoids energy-hole problem. The proposed approach has simulated using the Matlab R2012a simulator. Obtained results of the proposed approach RESA are compared with AODV routing algorithm on the basis of various metrics. Keywords: WBAN, MATLAB, Residual Energy, path loss. I. INTRODUCTION Wireless Sensor Networks (WSNs) are used to monitor certain parameters in many applications like environment monitoring, habitant monitoring, battle field, agriculture field monitoring and smart homes. These wireless sensors are dispersed in sensing area to monitor field. WBAN is new emerging sub-field of WSN. A key application of WBAN is health monitoring. Wireless sensors are placed on the human body or implanted in the body to monitor vital signs like blood pressure, body temperature, heart rate, glucose level etc. Use of WBAN technology to monitor health parameters significantly reduces the expenditures of patient in hospital. With the help of WBAN technology, patients are monitored at home for longer period. Sensors continuously sense data and forward to medical server. In WBANs, sensor nodes are operated with limited energy source. It is required to use minimum power for transmitting data from sensor nodes to sink. One of the major obstacles in WBAN is to recharge the batteries. An efficient routing protocol is required to overcome this issue of recharging batteries. Many energy efficient routing protocols are proposed in WSN technology. However, WSNs and WBANs have different architectures, applications and operate in different conditions. It is impossible to port WSN routing protocols to WBAN. Therefore, energy efficient routing protocol for WBAN is required to monitor patients for longer period. We propose a high throughput, reliable and stable routing protocol for WBAN. II. Related Work Body Area Networks is a network of sensor nodes implanted within the blood stream or on the body. Different available sensor nodes have different functionality. The idea of BAN comes from MIT, when different groups at MIT started working with the aim to develop something which can communicate between devices implanted on the human body. With this idea, they come to the All Rights Reserved 350

2 that electronic devices can communicate through capacitive coupling and eventually Body Area Networks is developed. BAN can be used for both medical and non-medical applications. General communication architecture for wireless sensor nodes in a Body Area Networks is suggested by Otto et al. [2] for health monitoring. In this paper, maximum numbers of nodes are stated 20 in wireless body area networks but generally they also suggested that number of nodes is not limited. Cluster-based Routing Protocol: (Anybody) Watteyne et al. [3] have proposed this self-organizing protocol. In this protocol, step by step routing is done through neighbor discovery, density calculation, contact cluster head, set up backbone and routing path. Probabilistic Routing Protocol: (DVRPLC) Quwaider et al. [4] have proposed Distance Vector Routing with Postural Link Costs. This protocol specifies a cumulative link cost factor for cost of routing over a link in some time slot. Cross-Layer Routing Protocol: (CICADA) Braem et al. [5] have proposed Controlling Access with Distributed Slot Assignment Protocol. It includes 2-way communication and improves reliability by considering multi-hop TDMA scheduling. Temperature based Routing: (TARA) Tang. et al. [6] have proposed Thermal Aware Routing Algorithm which follows withdrawal strategy in order to route packets from low temperature paths and reroutes from high temperature areas. QoS-based Routing: (DMQoS) Razzaque et al. [7] have proposed DMQoS, a data centric multi objective QoS aware routing protocol which provides customized QoS services according to different type of traffic generated. During the last 10 years, there has been number of research is going on and number of projects have been developed till now. Varied characteristics of Body Area Networks have raised number of issues which are necessary to consider during designing efficient routing protocol. Among all of these issues, In the context of routing protocols for Body Area Network minimum energy consumption is one of the critical issue because sensor nodes are implanted on the body or within the blood stream and frequent replacement of these batteries is not possible. One another import issue to deal with is hot-spot or energy hole problem. In the hot-spot problem, nodes which are closer to base station are used in most paths which leads to early use of their energy resources. Due to this, path from various nodes to the base station get disconnected and packet loss increases. III. MOTIVATION Mostly proposed routing algorithm for Body Area Networks works on the basis of Adhoc On- Demand Distance Vector protocol (AODV). AODV protocol was originally proposed in RFC AODV works on the concept of demand based routing. This protocol uses Route-Request (RREQ) packets, route request flooding only when the source wants to send data to some sink with unknown route. The two steps performed in AODV are route discovery and route maintenance. One of the disadvantages of AODV is that sometimes sensor nodes may experience a large delay in route discovery and construction and more bandwidth is consumed. In AODV, routing is mainly done only on the basis of minimum hop-count. But sometimes path with minimum hop-count is not energy efficient and choosing this path for routing causes more energy consumption. Energy-hole problem also exists in AODV as there is no support for minimum energy consumption. Our contribution includes: To implement an optimized Minimum energy consumption routing algorithm for BAN by considering some major metrics i.e. hop- count, residual energy and link quality for route discovery. To implement a self-adaptive routing algorithm i.e. which stores multiple paths for a single source to destination so that if some node becomes dead then it routes packet from different path. To eliminate the hot-spot or energy hole problem in the routing All Rights Reserved 351

3 IV. RESA: Protocol Detail & Results (a) Node Location : Node placement is achieved by deploying eight sensor nodes on human body. All sensor nodes have equal power and computation capabilities. Sink node is placed at waist. One node is ECG sensor node placed near sink. This node transmits data direct to sink. Other six sensors follow their parent node and transmit their data to sink through forwarder node. It saves energy of nodes and network works for longer period. The sink broadcast a short information packet which contains the location of the sink on the body. After receiving this control packet, each sensor node stores the location of sink. Each sensor node broadcasts an information packet which contains node ID, location of node on body and its energy status. In this way, all sensor nodes are updated with the location of neighbours and sink. In order to save energy and to enhance network throughput, we proposed a multi hop scheme for WBAN. we present selection criteria for a node to become parent node or forwarder. To balance energy consumption among sensor nodes and to trim down energy consumption of network, the choice of 150 cm is informed by using an average height of a person 150 cm. The forwarder node assigns a Time Division Multiple Access (TDMA) based time slots to its children nodes. All the children nodes transmit their sensed data to forwarder node in its own scheduled time slot. When a node has no data to send, it switches to idle mode. Nodes wake up only at its transmission time. Scheduling of sensor nodes minimize the energy dissipation of individual sensor node. (b) Radio Model: This model uses the distance(d) between the transmitter and the receiver and assumes the loss of energy due transmission channel(dxd). The model equations are shown below: ETx(k, d) = ETx elec(k) + ETx amp(k, d) ETx(k, d) = ETx elec k + Eamp k d2 (1) ERx(k) = ERx elec(k)erx(k) = ERx elec k ERx(k) = ERx elec k (2) where ETx is the energy consumed in transmission, ERx is the energy consumed by receiver, ETx elec and ERx elec are the energies required to run the electronic circuit of transmitter All Rights Reserved 352

4 receiver, respectively. Eamp is the energy required for amplifier circuit, while k is the packet size. In WBAN, the communication medium is human body which contributes attenuation to radio signal. Therefore, we add path loss coefficient parameter n in radio model. Equation 2 of transmitter can be rewritten as. ETx(k, d) = Eelec k + Eamp n k dn (3) The energy parameters given in equation 3 depend on the hardware. We consider two transceivers used frequently in WBAN technology. The Nordic nrf 2401A is a single chip, low power transceiver and other transceiver is Chipcon CC2420. The bandwidth of both transceivers is 2.4GHz. We use the energy parameter of The Nordic nrf 2401A transceiver because it consumes less power than Chipcon CC2420. The energy parameters for this transceiver are given below in Table. (c) Path loss: Path loss shows the relative strength between the transmitted power at the sending node and received power at the receiver. In general, path loss (returned in DB) is determined by average path loss modelling by: PL (d) = loss of path at d distance PL (do) = Path loss at a known distance do η = exponent for path loss Xσ = Random Variable with zero mean and σ All Rights Reserved 353

5 (d) Energy dissipation of radio model: The energy required to transmit data at a rate of 250kb/s for a period of 0.01 seconds. The energy consumption graph showed that the forwarder node and other six nodes can be placed at a distance of between 50cm and 75cm to achieve energy efficiency. V. PERFORMANCE METRICS Key performance metrics are evaluated for RESA protocol and the definition of these metrics is given in following subsections. A. Network lifetime: It represents the total network operation time till the last node die. In AODV, as temperature of forwarder nodes increases, nodes select alternate longer path which consumes more energy. Hence, these nodes die early. The proposed new cost function to elect forwarder node play an important role to balance the energy consumption among the sensor nodes. The proposed protocol has longer stability period. This is expected, due to the appropriate selection of new forwarder in each round. Hence, each node consumes almost equal energy in each round. Our proposed protocol achieves 31% more stability period and 0.4% longer network lifetime. B. Packet Delivery Ratio: It is the ratio of number of packets received at the destination nodes to the number of packets sent from the source nodes. Number of packets send to sink depends on the number of alive nodes. More alive nodes send more packets to sink which increases the throughput of network. The stability period of AODV is shorter than proposed protocol which means number of packets sent to sink decreased. Hence, throughput of AODV decreased. On the otherhand, proposed protocol achieves high throughput due to longer stability All Rights Reserved 354

6 C. Residual Energy: It is defined as the energy left with the nodes after a particular set of rounds traversed and is actually the difference in the initial energy and the utilized energy during network performance. In AODV, some nodes exhaust early due to heavy traffic load. The proposed protocol use multi hop topology, in which each farthest node transmits its data to sink through a relay node. To transfer packets to sink, our multi hop topology use different relay node in each round contributes to save energy, this restricts over loading of particular node. It means, in stability period, more nodes have enough energy and they transmit more data packet to sink. It also improves the throughput of the network. D. Path-loss: It is the difference between the transmitted power of transmitting node and received power at receiving node. It is measured in decibels (db). After 2000 rounds, path loss of AODV dramatically decreased because some nodes of AODV topology die. Minimum number of alive nodes has minimum cumulative path loss. As our proposed protocol has longer stability period and more alive nodes has more cumulative path loss. But initially proposed protocol performs well. Proposed multi hop topology reduces the path loss. It is due to the fact that multi hop transmission reduces the distance, which leads to minimum path All Rights Reserved 355

7 VI. CONCLUSION Proposed routing algorithm is self-adaptive as the residual energy keeps on updating itself. This algorithm is free from energy-hop or hot spot problem and has load balancing feature which avoids premature death of closer nodes to the sink as energy consumption is balanced and all nodes consume the same amount of accumulated energy over time. The proposed Reliable Energy Efficient Self-adaptive Algorithm gives more efficient(minimum energy consumption, i.e. residual energy increased about 5%) and reliable outcomes as compared to existing AODV routing algorithm for wireless body area networks. The proposed algorithm is evaluated using MATLAB R2012a simulation and compared with existing AODV. Obtained results conclude that the RESA algorithm is far better than existing AODV and has less energy consumption. RESA algorithm for just eight nodes increases the packet delivery ratio by 20% and decreases the energy consumption. The simulation is done for a smaller network, but in the case of larger networks RESA algorithm can be very helpful because reduced energy consumption directly increases the network lifetime. REFERENCES 1. S. Movassaghi, M. Abolhasan, J. Lipman, D. Smith, and A. Jamalipour, Wireless Body Area Networks: A Survey, In proceeding of IEEE Commun. Surv. Tutorials, vol. 16, no. 3, pp , C. Otto and a Milenkovic, System architecture of a wireless body area sensor network for ubiquitous health monitoring, In proceeding of Journal of Multimedia vol. 1, no. 4, pp , T. Watteyne, I. Augé-Blum, M. Dohler, and D. Barthel, AnyBody: a self-organization protocol for body area networks, In proceeding of Proc. Second Int. Conf. Body Area Networks BodyNets, M. Quwaider and S. Biswas, DTN routing in body sensor networks with dynamic postural partitioning, In proceeding of Ad Hoc Networks, vol. 8, no. 8, pp , B. Braem, B. Latre, C. Blondia, I. Moerman, and P. Demeester, Improving Reliability in Multi-hop Body Sensor Networks, In proceeding of Second Int. Conf. Sens. Technol. Appl. (sensor), pp , Q. Tang, N. Tummala, S. K. S. Gupta, and L. Schwiebert, Communication scheduling to minimize thermal effects of implanted biosensor networks in homogeneous tissue, In proceeding of IEEE Trans. Biomed. Eng., vol. 52, no. 7, pp , A. Razzaque, C. S. Hong, and S. Lee, Data-centric multiobjective QoS-aware routing protocol for body sensor networks, In proceeding of Sensors, vol. 11, no. 1, pp , Chenfu Yi, Lili Wang, and Ye Li, Member, IEEE, "Energy Efficient Transmission Approach for WBAN Based on Threshold Distance", In proceeding of IEEE Sensors Journal, Vol. 15, No. 9, Sep Himanshu Walia, Jasdeep Singh and Mandeep Singh, "Evaluation of AODV Routing Protocol under MANETS with Various Density Nodes", In proceeding of International Journal of Advanced Computer Research, Vol.-5, Issue-20,Sep Xianyue Wu, Yuriy I. Nechayev, Costas C. Constantinou and Peter S. Hall, Member, IEEE, "Interuser Interference in Adjacent Wireless Body Area Networks", In proceeding of IEEE Transactions On Antennas And Propagation, Vol. 63, No. 10, Oct B.Karthikeyan, N.Kanimozhi, S.Hari Ganesh, "Analysis of Reactive AODV Routing Protocol for MANET", In proceeding of IEEE World Congress on Computing and Communication All Rights Reserved 356

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