Adjacency Matrix Based Energy Efficient Scheduling using S-MAC Protocol in Wireless Sensor Networks

Communication is the main motive in any Networks whether it is Wireless Sensor Network, Ad-Hoc networks, Mobile Networks, Wired Networks, Local Area Network, Metropolitan Area Network, Wireless Area Network etc, hence it must be energy efficient. The main parameters for energy efficient communication are maximizing network lifetime, saving energy at the different nodes, sending the packets in minimum time delay, higher throughput etc. This paper focuses mainly on the energy efficient communication with the help of Adjacency Matrix in the Wireless Sensor Networks. The energy efficient scheduling can be done by putting the idle node in to sleep node so energy at the idle node can be saved. The proposed model in this paper first forms the adjacency matrix and broadcasts the information about the total number of existing nodes with depths to the other nodes in the same cluster from controller node. When every node receives the node information about the other nodes for same cluster they communicate based on the shortest depths and schedules the idle node in to sleep mode for a specific time threshold so energy at the idle nodes can be saved.Comment: 20 pages, 2 figures, 14 tables, 5 equations, International Journal of Computer Networks & Communications (IJCNC),March 2012, Volume 4, No. 2, March 201

A Comparative Study of Energy Efficient Medium Access Control Protocols in Wireless Sensor Networks

This project investigates energy usage in three energy-efficient WSN MAC protocols (AS-MAC, SCP-MAC, and Crankshaft) on TelosB wireless sensors. It additionally presents BAS-MAC, an energy-efficient protocol of our own design. Our evaluations show that in single-hop networks with large send intervals and staggered sending, AS-MAC is best in the local gossip and convergecast scenarios, while SCP-MAC is best overall in the broadcast scenario. We conjecture that Crankshaft would perform best in extremely dense hybrid (unicast and broadcast) network topologies, especially those which broadcast frequently. Finally, BAS-MAC would be optimal in networks which utilize hybrid traffic with infrequent broadcasts, and where broadcasting is performed by motes that do not have an unlimited power source

A Search Strategy of Level-Based Flooding for the Internet of Things

This paper deals with the query problem in the Internet of Things (IoT). Flooding is an important query strategy. However, original flooding is prone to cause heavy network loads. To address this problem, we propose a variant of flooding, called Level-Based Flooding (LBF). With LBF, the whole network is divided into several levels according to the distances (i.e., hops) between the sensor nodes and the sink node. The sink node knows the level information of each node. Query packets are broadcast in the network according to the levels of nodes. Upon receiving a query packet, sensor nodes decide how to process it according to the percentage of neighbors that have processed it. When the target node receives the query packet, it sends its data back to the sink node via random walk. We show by extensive simulations that the performance of LBF in terms of cost and latency is much better than that of original flooding, and LBF can be used in IoT of different scales

Transform-based Distributed Data Gathering

A general class of unidirectional transforms is presented that can be computed in a distributed manner along an arbitrary routing tree. Additionally, we provide a set of conditions under which these transforms are invertible. These transforms can be computed as data is routed towards the collection (or sink) node in the tree and exploit data correlation between nodes in the tree. Moreover, when used in wireless sensor networks, these transforms can also leverage data received at nodes via broadcast wireless communications. Various constructions of unidirectional transforms are also provided for use in data gathering in wireless sensor networks. New wavelet transforms are also proposed which provide significant improvements over existing unidirectional transforms

Effective scheduling algorithm for on-demand XML data broadcasts in wireless environments

The organization of data on wireless channels, which aims to reduce the access time of mobile clients, is a key problem in data broadcasts. Many scheduling algorithms have been designed to organize flat data on air. However, how to effectively schedule semi-structured information such as XML data on wireless channels is still a challenge. In this paper, we firstly propose a novel method to greatly reduce the tuning time by splitting query results into XML snippets and to achieve better access efficiency by combining similar ones. Then we analyze the data broadcast scheduling problem of on-demand XML data broadcasts and define the efficiency of a data item. Based on the definition, a Least Efficient Last (LEL) scheduling algorithm is also devised to effectively organize XML data on wireless channels. Finally, we study the performance of our algorithms through extensive experiments. The results show that our scheduling algorithms can reduce both access time and tuning time signifcantly when compared with existing work