Energy efficient clustering and secure data aggregation in wireless sensor networks

Communication consumes the majority of a wireless sensor network\u27s limited energy. There are several ways to reduce the communication cost. Two approaches used in this work are clustering and in-network aggregation. The choice of a cluster head within each cluster is important because cluster heads use additional energy for their responsibilities and that burden needs to be carefully distributed. We introduce the energy constrained minimum dominating set (ECDS) to model the problem of optimally choosing cluster heads in the presence of energy constraints. We show its applicability to sensor networks and give an approximation algorithm of O(log n) for solving the ECDS problem. We propose a distributed algorithm for the constrained dominating set which runs in O(log n log [triangle]) rounds with high probability. We show experimentally that the distributed algorithm performs well in terms of energy usage, node lifetime, and clustering time and thus is very suitable for wireless sensor networks. Using aggregation in wireless sensor networks is another way to reduce the overall communication cost. However, changes in security are necessary when in- network aggregation is applied. Traditional end-to-end security is not suitable for use with in-network aggregation. A corrupted sensor has access to the intermediate data and can falsify results. Additively homomorphic encryption allows for aggregation of encrypted values, with the result being the same as the result as if unencrypted data were aggregated. Using public key cryptography, digital signatures can be used to achieve integrity. We propose a new algorithm using homomorphic encryption and additive digital signatures to achieve confidentiality, integrity and availability for in- network aggregation in wireless sensor networks. We prove that our digital signature algorithm which is based on Elliptic Curve Digital Signature Algorithm (ECDSA) is at least as secure as ECDSA. Even without in-network aggregation, security is a challenge in wireless sensor networks. In wireless sensor networks, not all messages need to be secured with the same level of encryption. We propose a new algorithm which provides adequate levels of security while providing much higher availablility [sic] than other security protocols. Our approach uses similar amounts of energy as a network without security --Abstract, page iv

Energy Constrained Dominating Set for Clustering in Wireless Sensor Networks

Using partitioning in wireless sensor networks to create clusters for routing, data management, and other protocols has been proven as a way to ensure scalability and to deal with sensor network shortcomings such as limited communication ranges and energy. Choosing a cluster head within each cluster is important because cluster heads use additional energy for their responsibilities and that burden needs to be carefully passed around. Many existing protocols either choose cluster heads randomly or use nodes with the highest remaining energy. We introduce the energy constrained minimum dominating set (ECDS) to model the problem of optimally choosing cluster heads with energy constraints. We propose a distributed algorithm for the constrained dominating set which runs in O(log n log Δ) rounds with high probability. We experimentally show that the distributed algorithm performs well in terms of energy usage, node lifetime, and clustering time and, thus, is very suitable for wireless sensor networks

Implementation and Analysis of Practical Algorithm for Data Security

In this paper, we present a complete implementation of the Practical Algorithm for Data Security (PADS) proposed by Albath et al., an end-to-end security scheme employing symmetric key encryption. The implementation takes full advantage of the modular design of the TinyOS environment. The simplicity of the algorithm allows for efficient implementation in hardware, a requirement for resource constrained devices. The protocol adds only four bytes of data per packet, on par with industry standards. Simulation and empirical results of the scheme are also provided. The analysis shows that the Practical Algorithm for Data Security is superior to standard security schemes

Practical Algorithm for Data Security (PADS) in Wireless Sensor Networks

When data are generated in sensor networks, high-speed data streams travel through the network. Traditional security approaches are often unable to keep up with the rates of the streams or they introduce overhead, which shortens the life of the network. The approach proposed in this paper is one that solves the problems posed above. By embedding a one-time pad, the actual value is distorted enough to make any information gleaned from eavesdropping useless to an attacker. The use of the one-time pad ensures that the data were indeed received from a particular sensor, and it gives adequate protection against injected messages. The simulation shows this approach provides security with negligible overhead while the throughput is similar to the same network without security

RCC-3D: Qualitative spatial reasoning in 3D,”

Abstract Qualitative Spatial Reasoning (QSR) theories have applications in areas such as Geographic Information Systems (GIS), robotics, biomedicine, and engineering. However, existing QSR theories primarily have been applied only to 2D data. Herein we introduce a 3D reasoning system that is based on Generalized 2D Region Connection Calculus (GRCC). Our theory, RCC-3D, supports a priori knowledge of the extent of each object. It also provides occlusion support by considering the projections of 3D objects on 2D space. Further, we demonstrate how this model is applied to a particular domain such as anatomy