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

User data dissemination concepts for earth resources

Domestic data dissemination networks for earth-resources data in the 1985-1995 time frame were evaluated. The following topics were addressed: (1) earth-resources data sources and expected data volumes, (2) future user demand in terms of data volume and timeliness, (3) space-to-space and earth point-to-point transmission link requirements and implementation, (4) preprocessing requirements and implementation, (5) network costs, and (6) technological development to support this implementation. This study was parametric in that the data input (supply) was varied by a factor of about fifteen while the user request (demand) was varied by a factor of about nineteen. Correspondingly, the time from observation to delivery to the user was varied. This parametric evaluation was performed by a computer simulation that was based on network alternatives and resulted in preliminary transmission and preprocessing requirements. The earth-resource data sources considered were: shuttle sorties, synchronous satellites (e.g., SEOS), aircraft, and satellites in polar orbits

Performance evaluation of hierarchical ad hoc networks.

Ad hoc networking is one of the most challenging areas of wireless communication. Theoretical analysis and experimental results show that QoS (Quality of Service) for each node degrades rapidly while the number of nodes increases in the network. One way to solve performance degradation is to use hierarchical network architectures. In this paper, we investigate performance improvements offered by hierarchical ad hoc networks over flat (non-hierarchical or conventional) ad hoc networks for QoS parameters, namely throughput capacity, delay and power efficiency. We investigated and identified trade-offs among those QoS parameters via computer simulations carried by Network Simulator 2 of University of California (NS-2). In those simulations, we created hierarchical ad hoc networks by clustering the networks using cluster head nodes. Initially network is static (no mobility). Results of static network simulations act as benchmark for the performance parameters. Later mobility scenarios are added into the network to observe how mobility affects the performance. In order to compare two architectures, hierarchical and flat, we systematically changed number of nodes, data packet generation rates, number of clusters, node densities and transmission ranges for the nodes. At the same time, we compared hierarchical ad hoc network architecture with WLAN architecture, which has full infrastructure. Simulation results state that throughput performance is linear with numbers of clusters; and in hierarchical architecture, power efficiency is doubled and delay is significantly lower than flat architecture. Our simulation results conclude that clustering schemes in wireless ad hoc networks can solve the scalability problem that exists in flat architectures.Dept. of Electrical and Computer Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2005 .Y83. Source: Masters Abstracts International, Volume: 44-01, page: 0499. Thesis (M.A.Sc.)--University of Windsor (Canada), 2005

Computer Aided Verification

The open access two-volume set LNCS 11561 and 11562 constitutes the refereed proceedings of the 31st International Conference on Computer Aided Verification, CAV 2019, held in New York City, USA, in July 2019. The 52 full papers presented together with 13 tool papers and 2 case studies, were carefully reviewed and selected from 258 submissions. The papers were organized in the following topical sections: Part I: automata and timed systems; security and hyperproperties; synthesis; model checking; cyber-physical systems and machine learning; probabilistic systems, runtime techniques; dynamical, hybrid, and reactive systems; Part II: logics, decision procedures; and solvers; numerical programs; verification; distributed systems and networks; verification and invariants; and concurrency

Computer Aided Verification

This open access two-volume set LNCS 11561 and 11562 constitutes the refereed proceedings of the 31st International Conference on Computer Aided Verification, CAV 2019, held in New York City, USA, in July 2019. The 52 full papers presented together with 13 tool papers and 2 case studies, were carefully reviewed and selected from 258 submissions. The papers were organized in the following topical sections: Part I: automata and timed systems; security and hyperproperties; synthesis; model checking; cyber-physical systems and machine learning; probabilistic systems, runtime techniques; dynamical, hybrid, and reactive systems; Part II: logics, decision procedures; and solvers; numerical programs; verification; distributed systems and networks; verification and invariants; and concurrency