In every locality we build a Gray cube with locally adapted dimension.
Our RD is based on virtual network backbone created by dividing the network into several non overlapping localities using multi-hop clustering. We propose an efficient and scalable RD architecture to meet the challenging requirements of reliable, scalable and power-efficient RD protocol suitable for MANETs with potentially thousands of wireless mobile devices. One of the major challenges in MANET is RD protocols responsible for advertising and searching network services. MANET is an autonomous system of mobile nodes characterized by wireless links. The study conducted a primary investigation into using the Gray cube structure, clustering and Distributed Hash Tables (DHTs) to build an efficient virtual network backbone for Resource Discovery (RD) tasks in large scale Mobile Ad hoc NET works (MANETs). Detailed statistics on the outcome of these experiments are provided which show clearly the practical utility of the labeling approach. To confirm our theoretical findings we conduct various experiments with randomly selected P2P networks of various sizes. We prove that the labeling scheme does in fact allow for reducing bandwidth utilization in the network. The labels allow for creating a virtual overlay which resembles a hypercube. To realize such a hypercube-like engineered structure, we develop a new labeling scheme which assigns identifiers (labels) to each node and then uses these labels to determine inter-node distances as is done in a hypercube, thus eliminating the need to send out queries to find the distance from one node to another. The reason for doing this is to achieve constant computation time for inter-node distances that are needed in the process of query optimization. In particular, we exploit the characteristics of a P2P network engineered to resemble a hypercube. This paper addresses the general problem of reducing unnecessary message transmission thereby lowering overall bandwidth utilization in a Peer-to-Peer (P2P) network. The evaluation shows that the differential indexing approach has better performance than the non-indexing and index-based approaches in terms of total energy consumption and total elapsed time. Otherwise, it sends the corresponding index for this sensed reading in the indexing table. When the SN wants to send a sensed reading, it sends its location in the lookup table represented by the least number of bits (which will have shorter length than the length of corresponding index for the sensed reading in the indexing table), if it exists in the lookup table. For each newly sensed reading, this number is increased by one. Then, it starts giving a number for each sensed reading. This approach first assigns an index for each possible value for a sensed reading. In this paper, a differential indexing approach is proposed to reduce the consumed energy and as a result the batteries of SNs will last longer. Therefore, the energy consumption must be reduced in order to make the batteries live longer. In wireless sensor networks (WSNs), the sensor nodes (SNs) have batteries with limited energy. We analyze the performance of our scheme and conduct a comparative study to demonstrate its superiority compared to other schemes proposed recently in the literature. The proposed scheme achieves both objectives as it reduces the power consumption and provides minimum delay as well as providing better scalability, efficiency and fault tolerance. Moreover, we provide an efficient construction mechanism for the virtual backbone. In this paper, we propose a novel scheme for data gathering based on the pyramid interconnection that uses the pyramid as a virtual backbone and collects data from all sensors to the base station upwards. Due to the limited battery power and criticality of the applications in most cases, methods employed for data gathering and aggregation need to be power efficient and with minimum delay in order to achieve longer network lifetime and be effective. Consequently, the sensed data must be gathered by the nodes and transmitted to a base station for further processing. Wireless sensor networks are deployed to collect useful information from an area of interest.
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