Walid Osamy

IBLEACH: intra-balanced LEACH protocol for wireless sensor networks

Wireless sensor networks (WSNs) are composed of many low cost, low power devices with sensing, local processing and wireless communication capabilities. Recent advances in wireless networks have led to many new protocols specifically designed for WSNs where energy awareness is an essential consideration. Most of the attention, however, has been given to the routing protocols since they might differ depending on the application and network architecture. Minimizing energy dissipation and maximizing network lifetime are important issues in the design of routing protocols for WSNs. In this paper, the low-energy adaptive clustering hierarchy (LEACH) routing protocol is considered and improved. We propose a clustering routing protocol named intra-balanced LEACH (IBLEACH), which extends LEACH protocol by balancing the energy consumption in the network. The simulation results show that IBLEACH outperforms LEACH and the existing improvements of LEACH in terms of network lifetime and energy consumption minimization.

Perimeter discovery in wireless sensor networks

In this paper, we focus on the perimeter detection problem using wireless sensor networks, as perimeter detection has a wide range of uses in several areas. We present a decentralized localized algorithm where sensor nodes determine if they are located along the perimeter of a wireless sensor network. Our proposed algorithm uses the location neighborhood information in conjunction with the Barycentric technique to determine if the sensor node enclosed by neighboring nodes, and consequently, if it is located within the interior of the wireless sensor network. We define performance metrics to analyze the performance of our approach and the simulation shows that the algorithm gives fairly accurate results.

Effective target tracking mechanism in a self-organizing wireless sensor network

Abstract Target tracking is an important sensing application of wireless sensor networks. In these networks, energy, computing power, and communication bandwidth are scarce. We have considered a random heterogeneous wireless sensor network, which has several powerful nodes for data aggregation/relay and large number of energy-constrained sensor nodes that are deployed randomly to cover a given target area. In this paper, a cooperative approach to detect and monitor the path of a moving object using a minimum subset of nodes while maintaining coverage and network connectivity is proposed. It is tested extensively in a simulation environment and compared with other existing methods. The results of our experiments clearly indicate the benefits of our new approach in terms of energy consumption.

Minimum perimeter coverage of query regions in a heterogeneous wireless sensor network

Abstract Many applications of wireless sensor networks (WSNs) require the tracking and the surveillance of target objects. The information to be gathered about the target may be related to only a particular monitored sub-area. Therefore, it is desirable to direct queries only to the nodes monitoring this particular area and for energy saving reasons, only the queried nodes should respond. In this paper, we introduce two new efficient distributed algorithms for finding the minimum number of connected perimeter sensor nodes that are sufficient to cover the perimeter of queried region, where the union of their sensing regions covers the perimeter of queried area. The simulation results show that our proposed algorithms achieve significant reduction in communication load, while preserving full perimeter coverage.

A topology discovery algorithm for sensor network using smart antennas

Wireless sensor networks have recently attracted lots of research effort due to its wide range of applications. In this paper, we focus on sensor network topology discovery problem, where accurate network topology information is important for both network management and application performance prediction. We present on demand algorithm to discover the sensor network topology. The node that receives our topology request collects all topology related information from each node in the network and constructs link information databases.

Mobility-assisted minimum connected cover in a wireless sensor network

All properties of mobile wireless sensor networks (MWSNs) are inherited from static wireless sensor networks (WSNs) and meanwhile have their own uniqueness and node mobility. Sensor nodes in these networks monitor different regions of an area of interest and collectively present a global overview of monitored activities. Since failure of a sensor node leads to loss of connectivity, it may cause a partitioning of the network. Adding mobility to WSNs can significantly increase the capability of the WSN by making it resilient to failures, reactive to events, and able to support disparate missions with a common set of sensor nodes. In this paper, we propose a new algorithm based on the divide-and-conquer approach, in which the whole region is divided into sub-regions and in each sub-region the minimum connected sensor cover set is selected through energy-aware selection method. Also, we propose a new technique for mobility assisted minimum connected sensor cover considering the network energy. We provide performance metrics to analyze the performance of our approach and the simulation results clearly indicate the benefits of our new approach in terms of energy consumption, communication complexity, and number of active nodes over existing algorithms.

Minimum connected cover of a query region in heterogeneous wireless sensor networks

Wireless sensor networks are composed of a large number of tiny sensors that have limited resources and yet must form a connected network. The main challenge in the design of sensor networks is the limited battery power of the sensors and the difficulty of replacing and/or recharging these batteries due to the nature of the monitored field. Thus, it is necessary that the sensors be densely deployed and energy-efficient protocols be designed to maximize the network lifetime while meeting the specific application requirements in terms of coverage and connectivity. Given a query over a sensor network the minimum connected sensor cover problem is to select a minimum, or nearly minimum, set of sensors such that the selected sensors cover the query region and form a connected network. In this paper, we propose a new distributed algorithm to find the minimum connected cover of the queried region for heterogeneous sensors, each with arbitrary sensing and transmission radii and different energy levels. Each sensor node in the network determines whether to sense the queried region according to its minimum-weight coverage cost. We provide performance metrics to analyze the performance of our approach and the simulation results show that our approach clearly improves the network lifetime over existing algorithms.

Distributed multi chain compressive sensing based routing algorithm for wireless sensor networks

In wireless sensor networking applications, collecting sensed data and relaying it to the base station in an energy efficient manner is of paramount importance. It follows that power management and energy-efficient communication techniques become necessary to maximize network lifetime for wireless sensor networks (WSNs). In this paper, our objective is to distribute energy consumption evenly and maximize the network lifetime by utilizing data aggregation and in-network compression technique. We mainly focus on the combined problem of data routing with data aggregation during routing such that minimizing the number of packets to transmit and achieve our objective. We propose a multi chain routing algorithm executed with compressive sensing for data aggregating in WSNs. We show that by using our compressive sensing based routing algorithm significant reduction in data traffic can be achieved, resulting in power saving and thus prolong the network lifetime.

Sparse Signals Reconstruction via Adaptive Iterative Greedy Algorithm

Compressive sensing(CS) is an emerging research field that has applications in signal processing, error correction, medical imaging, seismology, and many more other areas. CS promises to efficiently reconstruct a sparse signal vector via a much smaller number of linear measurements than its dimension. In order to improve CS reconstruction performance, this paper present a novel reconstruction greedy algorithm called the Enhanced Orthogonal Matching Pursuit (E-OMP). E-OMP falls into the general category of Two Stage Thresholding(TST)-type algorithms where it consists of consecutive forward and backward stages. During the forward stage, E-OMP depends on solving the least square problem to select columns from the measurement matrix. Furthermore, E-OMP uses a simple backtracking step to detect the previous chosen columns accuracy and then remove the false columns at each time. From simulations it is observed that E-OMP improve the reconstruction performance better than Orthogonal Matching Pursuit (OMP) and Regularized OMP (ROMP).