Enhancing the life time of sensor network with energy awareness and clutter adaptability

Wireless sensor networks encompass wide variety of applications those claim the sensing and communication of parameters simultaneously in well-defined regions of interests. But these networks would most likely have failures in communication due to the destruction of sensor nodes by sudden deployment from the aircraft or battery exhaustion. This curtailment of data forwarding by the ineffective nodes creates holes in the networks. For maintaining effectiveness of the networks these holes must be detected and healed. These networks are usually formed in areas those conceal high risks denying human aid for their maintenance necessitating the network, to adopt a self-organizing or a reorganizing strategy to ensure its fidelity. Various methods were developed so far for detection and healing of coverage holes in the network. These were either interpreted in unrealistic or more complex modes. In this scenario HEAL advanced as an effective solution to detect and heal the holes using the simple concepts of virtual forces. The HEAL is a light weight algorithm with lesser computation, mends for localized healing and designed to operate in two phases 1) hole detection 2) hole healing. The detection of hole is done using TENT rule. The areas of curtailed communications were effectively mended using the attractive and repulsive forces in mobile nodes homogeneous environment. Here mobility of nodes plays key role in maintaining network efficiency utilizing the ability to movements to reorganize the network. Though HEAL out performs all the existing algorithms it paved ways for further improvements. Thus an algorithm named Energy Heal has been proposed here as a modified version of its predecessor. It also possess two phases, were the first phase hole detection is similar to heal. The second phase is advanced hole healing based on energy of nodes, where nodes with energy greater than a predefined threshold is only taking part in the healing scenario leaving behind positive traces for a much more improved network life time. Another drawback of Heal is that it did not give any platforms for the clutters though the chances for their presence cannot be marginalized. This special case is considered here alongside with ENERGY HEAL. Simulations are carried out using network simulator to validate heal and its proposed successor. A comparative study carried so far brings out positive curves for ENERGY HEAL in terms of network coverage as well as node movements in cases where nodes would densely dwell.