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An Analysis of Real Time Routing Protocols for Wireless Sensor Networks

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An Analysis of Real Time Routing

Protocols for Wireless Sensor Networks

Sandhya Bansal1, Dr Dimple Juneja2, Dr Saurabh Mukherjee3

1,2

MM University, Mullana, Haryana, India.3 Banasthali University,Rajasthan, India

Abstract:

Recent advances in Wireless Sensor Networks (WSN’s) have lead to rapid development of real time applications. Many routing protocols are designed for these applications where timely delivery of the message is of utmost importance. This paper presents comparative analysis of various existing real time routing protocols in wireless sensor networks, emphasizing their strengths and weaknesses and various challenges have been highlighted for future research.

Keywords: Wireless Sensor Network, Real Time systems (RT’s), Routing Protocols.

1. Introduction

With the continuously growing wireless technologies, WSN’s [2] have emerged as a popular area of research. Recent use of WSN’s in real time applications lead to the need of focusing research towards routing protocols. Real time routing must find a path from source to destination which meets time constraints. Real time sensor systems have many applications especially in intruder detection, medical care, and fire monitoring and health diagnosis [11]. In these applications, timely and reliable delivery of the data is very important for positive results as out-dated data will lead to disaster effects. Without loss of generality, real time systems are categorized as hard real time and soft real time systems. In hard real time systems, deterministic end to end delay bound is required otherwise catastrophic results will occur while on the other hand in case of soft real time system some delay is tolerable i.e probabilistic results are accepted. A classification of the same is given in figure 1. The significant features of these protocols have been highlighted in Section 2.

Figure 1. Classification of Real Time Routing Protocols in WSN

Integrating characteristics of both WSN’s and RT’s is a challenging task as former is energy constrained while later imposes temporal constrained. It is evident that both of these constraints are inversely proportional to each other. To deliver the message on time sensor should use their maximum transmission power, which drains

Real Time Routing Protocols in WSN’s

Hard Real Time Soft Real Time

I-EDF

Dual-Mode MAC

RAP

SPEED

MMSPEED

FT-SPEED

RPAR

EA-QoS

RTPA

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energy. Also, real time routing in WSN’s is different from their counterparts because of their limited resources, dynamic topology, less reliable nature, dense deployment. It has been proved that work done in wired network [17] [21] cannot be applied directly to meet the challenges of real time routing in WSN.

The remainder of the article is organized as follows. Section 2 aims to provide a survey on the state of the art of related routing protocols along with comparison of existing solutions on different parameters. The challenges and conclusions are discussed in Section 3.

2. Current Solutions for Real Time Routing in WSN’s

This section highlights the work of eminent researchers who had made attempts to provide solutions for routing in WSN. [20, 18, 16, 14] are best effort protocols that provides services at MAC layer but none of them had taken the tradeoff between energy and delay into account which is the major goal of real time sensor communication.

Work in [4] proposes an implicit prioritized access protocol (I-EDF), for deterministic RTs which demands prior topological information and synchronization. However, this is not suitable in non-deterministic environments.

Watteyene et al. [19] proposes a dual-mode MAC that supports HRT’s with relaxed conditions than I-EDF. Deployed nodes operate in protected and unprotected mode. A protected mode is set on whenever a collision detected, else the node remains in unprotected mode. In protected mode cellular network time synchronizations are required, that are difficult to meet and moreover energy metric had not taken into consideration.

In contribution to these efforts, Pothuri et al. [7] proposed a PEDAMACS, a heuristic solution to find energy efficient path from source to sink along which delay incurred should be less. For this author had indexed and ordered so as to provide a path that returns end-to-end delay. However the assumptions such as each node should have two radios, stationary nodes are impractical.

Now turning attention towards protocols for soft real time systems ChenyangLu et al. [13] proposes the first architecture (RAP) that handles deadline issues pertaining to soft real time systems. It not only uses high level query and event services for meeting the deadlines but also it uses the novel Velocity Monotonic Scheduling (VMS) policy to schedule the packets. This protocol is scalable as geographic forwarding is used. Also Mobility of the sensor node is taken into account. On the other side energy and reliability aspects of the protocol are also important research directions.

SPEED [10] provides soft end-to-end deadline for real time systems. It combines feedback control and nondeterministic QoS-aware geographic forwarding such that each packet can be routed without global topology information. This protocol is scalable as every mechanism works in a localized manner. Moreover speed is uniformly distributed all over the network which helps in prediction about the end-to-end deadline. This protocol also handles void problems. However, the protocol provides only one network-wide speed, which is not suitable for differentiating various traffic having different deadlines. In addition, it doesn’t consider energy metric and reliability in its routing protocol.

MMSPEED [8] extends SPEED to support different velocities and level of reliability for probabilistic QoS guarantee in WSN. Geographic forwarding and multiple QoS levels are used to provide scalability and differentiated QoS options in timeliness and reliability domains. This protocol is augmented with dynamic compensation for inaccuracies of local decision. Advantages of this protocol are that it is scalable to very large and dense networks, suitable for both a periodic and periodic traffic. On the downfall side energy metric is not taken into account and it fails when packet reaches the void in network topology.

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real time routing for supporting energy efficient real time communication. This protocol is related to SPEED, and MMSPEED. Moreover it can handle lossy links.

In this paper [1] author proposes an energy-aware QoS routing protocol for sensor networks which can also run efficiently with best-effort traffic. The protocol finds a least-cost, delay-constrained path for real-time data in terms of link cost that captures nodes’ energy reserve, transmission energy, error rate and other communication parameters. Moreover, the throughput for non-real-time data is maximized by adjusting the service rate for both real-time and non-real-time data at the sensor nodes.

Real Time communication with Power Adaption (RTPA) [3] is a novel routing scheme that provides efficient power consumption and the desired quality of service (QoS) in WSN. It extends the previous work to achieve low end to-end delay, low power consumption, reduced overhead in control packet flow, good throughput, less interference and channel contention. A key advantage of RTPA is that it can deliver packets within their end-to-end deadlines, while minimizing the network power consumption by adapting the transmission power based on the timing requirements of the workload and link quality between the source and destination. RTPA uses the IEEE 802.15.4 MAC and physical layers standard.

Directional geographic routing [5] solves the problem of H.26L real time video communication over a bandwidth and energy constraint WSN. The limited bandwidth of WSN does not allow compressed video along with FEC coding to transmit form source to sink with minimum delay. To encounter this problem, multipath routing is used in DRG to support the delivery of multiple flows. But DRG algorithm assumes that at a time only one sensor will transmit the data that is not realistic.

PATH, A novel real time Power Aware Two Hope [15] based routing protocol that improves real time performance by means of dropping packets in routing decision. For routing information it uses two hop neighbor information and power control mechanism to reduce power and delay.

Dynamically jumping Real time Fault tolerant protocol (DMFR) [9] routes the packets according to five stages: initialization, data transmission, jumping transmission, jumping probability adjustment and transmission finish. In this protocol transition from transmission phase to jumping stage occurs when there exists a faulty, congested node. To increase the ratio of successful transmission each node dynamically adjusts its jumping probabilities.

A vital look at the above literature indicates the birth and hence expansion of various protocols on one or other parameters. Table 1 below summarizes routing protocols for hard real time systems (HRT’s).

Table 1. Comparison of HRTs Routing Protocols.

Protocols MAC Type Topology Factors Considered

I-EDF TDMA-FDMA Cellular None.

Dual-Mode TDMA-FDMA Cellular None

PEDAMACS TDMA No Energy

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Table 2. Comparison of SRTs Routing Protocols

Protocols Protocol Operation Factors Considered Performance Metrics

RAP Query, Location Mobility, Scalability End-to-end deadline miss ratio

SPEED Location Scalability Delay

MMSPEED Location Scalability, Reliability Average Delay, Overhead, reliability

FT-SPEED Location Fault Tolerance Packet Delivery, Average Delay

RPAR N/A Energy, Power, Lossy Links,

Scalability ,Bandwidth

Deadline Missed, Energy consumption

EA-QoS Hierarchical Energy, Reliability Average life time of node, Average Delay per packet, Throughput

RTPA Location Energy, Power, Link Quality End-to-end delay, Overhead Throughput

DRG Hierarchical Energy, Reliability Network Life time,

Average end-to-end delay, Energy Consumption, PSNR

PATH Location Energy, Power, Reliability Delay, Deadline Miss Ratio Energy Consumption.

DMRF N/A Reliability, Lossy Links,

Energy

Successful Transmission, Average Delay

Table 2 represents the comparison of routing protocols for soft real time systems. Comparison is done on the basis of protocol operation, factors such as energy, scalability, lossy links, reliability etc. and metrics taken for performance measurement. It was observed that protocols that uses location awareness are scalable and that uses hierarchical operation are reliable in nature.

3. Challenges and Conclusions

Drilling the above literature and comparisons, it is apparent that a protocol integrating various parameters such as energy, bandwidth, buffer size, processing capabilities is strongly desired. Further it is recommended that such a protocol should not only meet QoS standards but also should be robust, extensible and must support cross layer design. Cross layer design demands a merging of protocols at different layers while maintaining the simplicity of network. An analytical study of various hard real time and soft real time routing protocols in WSN has been performed. The study revels that soft real time routing dominates hard real time routing protocol in terms of deadline flexibility. It is also concluded that energy metric in WSN is inversely proportional to time domain in real time systems.

References

[1] Akkayk and Younis M, “An Energy-Aware QoS Routing Protocol for Wireless Sensor Networks,” in the Proceedings of the IEEE Workshop on Mobile and Wireless Networks (MWN2003) [C], Providence, Rhode Island, May 2003.

[2] Akyildiz I, Su W and Sankarasubramaniam Y et al., “Wireless sensor networks: a survey,” Computer Networks [J], Vol. 38,pp.393-442, March 2002.

[3] Ali, A., Latiff, L. A., Rahid, R. A., Fisal, N “ Real time communication with power adaptation (RTPA) in wireless sensor network (WSN)” 2006 International Conference on Computing and Informatics ICOCI 06.

[4] Caccamo, M., L.Y. Zhang, L. Sha and G. Buttazzo “An implicit prioritized access protocol for wireless sensor networks”. In: Proc. 23rd

IEEE RTSS. pp. 39-48, 2002.

[5] Chen M, Leung V and Mao S et al., “Directional geographical routing for real-time video communications in wireless sensor networks”, Computer Communication [J], 30 (2007), p.3368-3383, 2007.

[6] Chipara O, He Z and Xing et al., “Real-time Power-Aware Routing in Sensor Networks,” in the Proceedings of the 14th IEEE International Workshop on Quality of Service (IWQoS 2006) [C], New Haven, CT, June 2006.

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[9] Guowei Wu , Chi Lin , Feng Xia , Lin Yao , He Zhang, and Bing Liu “Dynamical Jumping Real-Time Fault-Tolerant Routing Protocol for Wireless Sensor Networks”, Sensor 2010 .

[10] He T, Stankovic J and Lu C et al., “SPEED: A stateless protocol for real-time communication in sensor networks,” in the Proceedings of International Conference on Distributed Computing Systems [C], Providence, RI, May 2003.

[11] Li Y, Chen C and Song Y et al., “Real-time QoS support in wireless sensor networks: a survey,” in the Proceedings of 7th IFAC Int Conf on Fieldbuses & Networks in Industrial & Embedded Systems (FeT’07) [C], Toulouse, France, Nov 2007.

[12] Lei, Z.; Kan, B.Q.; Xu, Y.J.; Li, X.W “FT-SPEED: A fault-tolerant, real-time routing protocol for wireless sensor networks”. In Proceedings of 2007 International Conference on Wireless Communications, Networking and Mobile Computing, Shanghai, China, pp. 2531–2534, 2007.

[13] Lu C, Blum B and Abdelzaher T et al., “RAP: A Real-time Communication Architecture for Large-Scale Wireless Sensor Networks,” in the Proceedings of the Eighth IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS’ 02) [C], 2002. [14] Lu, G., B. Krishnamachari and C.S. Raghavendra “An adaptive energy-efficient and low-latency MAC for data gathering in wireless

sensor networks”. In: Proc. Int. Parallel Distrib. Process. Symp. pp. 224-231, 2004.

[15] Parvaneh Rezayat, Mehdi Mahdavi, Mohammad Ghasemzadeh, Mehdi Agha Sarram, “ A Novel Real-Time Power Aware Routing Protocol in Wireless Sensor Networks,” IJCSNS International Journal of Computer Science and Network Security, VOL.10 No.4, April 2010.

[16] Polastre, J., J. Hill and D. Culler “ Versatile low power media access for wireless sensor networks. In: Proc. ACM Sensys. pp. 95-107, 2004.

[17] Stankovic J, Abdelzahert and Lu C et al., “Real-time communication and coordination in embedded sensor networks,” in the proceedings of IEEE 91(7) [C], 1002-1022.

[18] Van Dam, T. and K. Langendoen “An adap-tive energy-efficient MAC protocol for wireless sensor networks”. In: Proc. ACM Sensys, 2003.

[19] Watteyne, T., I. Auge-Blum and S. Ubeda “Dual-mode real-time MAC protocol for wireless sensor networks: a validation/simulation approach”. In: Proc. InterSense, 2006.

[20] Ye, W., J. Heidemann and D. Estrin. “Medium access control with coordinated adaptive sleeping for wireless sensor net-works”. IEEE/ACM Trans. Netw. 12(3), 493- 506, 2004.

[21] Zhao W, Stankovic J and Ramamritham K, “A Window Protocol for Transmission of Time-Constrained Messages,” IEEE Transactions on Computers [J], 39(9), p.1186-1203, September 1990.

Figure

Figure 1. Classification of Real Time Routing Protocols in WSN
Table 2. Comparison of SRTs Routing Protocols

References

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