VAMPIRE DETECTION IN DATA AGGREGATION PROCESS FOR WSN

Wireless sensor networks have emerged as a new information-gathering paradigm in a wide range of applications, such as medical treatment, battlefield surveillance, emergency response, etc. This paper proposes a new data-gathering mechanism for large-scale wireless sensor networks by introducing mobility into the network. A mobile data collector, for convenience called an M-collector, could be a mobile robot or a vehicle equipped with a powerful transceiver and battery, working like a mobile base station and gathering data while moving through the field. An M-collector starts the data-gathering tour periodically from the static data sink, polls each sensor while traversing its transmission range, then directly collects data from the sensor in single-hop communications, and finally transports the data to the static sink. Deployment of sensor network in hostile environment makes it mainly vulnerable to battery drainage . The motivation of a large portion of research efforts has been to maximize the network lifetime, where the lifetime of network is measured from the instant of deployment to the point when one of the nodes has exhausted its limited power source and becomes in- operational commonly referred as first node failure. But there is a class of resource consumption attack called vampire attack which permanently disables the whole network by quickly draining nodes battery. Forwarding as well as discovery phase of the protocol are considered to avoid an attack. Discovery phase is considered to avoid vampire attack.

[1]  Ian F. Akyildiz,et al.  Sensor Networks , 2002, Encyclopedia of GIS.

[2]  Chi Ma,et al.  A Battery-Aware Scheme for Routing in Wireless Ad Hoc Networks , 2011, IEEE Transactions on Vehicular Technology.

[3]  John Anderson,et al.  Wireless sensor networks for habitat monitoring , 2002, WSNA '02.

[4]  Leandros Tassiulas,et al.  Maximum lifetime routing in wireless sensor networks , 2004, IEEE/ACM Transactions on Networking.

[5]  Zygmunt J. Haas,et al.  The shared wireless infostation model: a new ad hoc networking paradigm (or where there is a whale, there is a way) , 2003, MobiHoc '03.

[6]  Yuanyuan Yang,et al.  Tour Planning for Mobile Data-Gathering Mechanisms in Wireless Sensor Networks , 2013, IEEE Transactions on Vehicular Technology.

[7]  Wei Wang,et al.  Using mobile relays to prolong the lifetime of wireless sensor networks , 2005, MobiCom '05.

[8]  L. Javier García-Villalba,et al.  Routing Protocols in Wireless Sensor Networks , 2009, Sensors.

[9]  Nicholas Hopper,et al.  Vampire Attacks: Draining Life from Wireless Ad Hoc Sensor Networks , 2013, IEEE Transactions on Mobile Computing.

[10]  Djamal Zeghlache,et al.  Multiple Mobile Sinks Deployment for Energy Efficiency in Large Scale Wireless Sensor Networks , 2008, ICETE.

[11]  Ji Luo,et al.  Delay Tolerant Event Collection in Sensor Networks with Mobile Sink , 2010, 2010 Proceedings IEEE INFOCOM.

[12]  Ashutosh Sabharwal,et al.  Using Predictable Observer Mobility for Power Efficient Design of Sensor Networks , 2003, IPSN.

[13]  Leonidas J. Guibas,et al.  Data stashing: energy-efficient information delivery to mobile sinks through trajectory prediction , 2010, IPSN '10.

[14]  Peter I. Corke,et al.  Data collection, storage, and retrieval with an underwater sensor network , 2005, SenSys '05.

[15]  Sandeep K. S. Gupta,et al.  Research challenges in wireless networks of biomedical sensors , 2001, MobiCom '01.

[16]  Yong Wang,et al.  Energy-efficient computing for wildlife tracking: design tradeoffs and early experiences with ZebraNet , 2002, ASPLOS X.

[17]  Carlos F. García-Hernández,et al.  Wireless Sensor Networks and Applications: a Survey , 2007 .

[18]  John A. Stankovic,et al.  Wireless Sensor Networks , 2008, Computer.

[19]  Laura Marie Feeney,et al.  An Energy Consumption Model for Performance Analysis of Routing Protocols for Mobile Ad Hoc Networks , 2001, Mob. Networks Appl..

[20]  Krishna M. Sivalingam,et al.  Data Gathering Algorithms in Sensor Networks Using Energy Metrics , 2002, IEEE Trans. Parallel Distributed Syst..

[21]  Sugata Sanyal,et al.  Sleep Deprivation Attack Detection in Wireless Sensor Network , 2012 .

[22]  Stefano Chessa,et al.  Crash faults identification in wireless sensor networks , 2002, Comput. Commun..