Clustering Based Topology Control Protocol for Data Delivery in Wireless Sensor Networks

The issue of optimizing the limited and often non-renewable energy of sensor nodes due to its direct impact on network lifetime dominates every aspect of wireless sensor networks. Existing techniques for optimizing energy consumption are based on exploiting node redundancy, adaptive radio transmission power and topology control. Topology control protocols have a significant impact on network lifetime, available energy and connectivity. In this paper we classify sensor nodes as strong and weak nodes based on their residual energy as well as operational lifetime and propose a Clustering based topology control protocol (CTCP) which extends network lifetime while guarantying the minimum connectivity. Extensive simulations in Java-Simulator (J-Sim) show that our proposed protocol outperforms the existing protocols in terms of various performance metrics life network lifetime, average delay and minimizes energy utilization.Comment: 12 pages, 4 figures; International Journal of Computer Science and Issues. January 201

Reliable Robust and Real-Time Communication Protocol for Data Delivery in Wireless sensor Networks

WSNs can be considered a distributed control system designed to react to sensor information with an effective and timely action. For this reason, in WSNs it is important to provide real-time coordination and communication to guarantee timely execution of the right actions. In this paper a new communication protocol RRRT to support robust real-time and reliable event data delivery with minimum energy consumption and with congestion avoidance in WSNs is proposed. The proposed protocol uses the fault tolerant optimal path for data delivery. The proposed solution dynamically adjust their protocol configurations to adapt to the heterogeneous characteristics of WSNs. Specifically, the interactions between contention resolution and congestion control mechanisms as well as the physical layer effects in WSNs are investigated.Comment: 15 pages, 6 figure

Comparison of Proposed Data Dissemination Protocols for Sensor Networks Using J-Sim

A distinguishing characteristic of wireless sensor networks is the opportunity to exploit characteristics of the application at lower layers. This paper reports on the results of a simulation comparison of proposed data dissemination protocols using the J-Sim simulator for the WSN protocols: Forwarding Diffusion Data Dissemination(FDDDP), Decentralized Data Dissemination(DDDP), Credit Broadcast Data Dissemination (CBDDP), Energy Aware & Geographical Data Dissemination (EAGDDP) .Our performance provides useful insights for the network designer such as which protocols (and design choices) scale control traffic well, improve data delivery or reduce overall energy consumption,improves routing overhead and maximizes the bandwidth utilization. The static pre configuration of the cell size in DDDP, is one of the reasons why DDDP exhibits larger routing overhead than FDDDP by 74.2% on average. Although CBDDP produces approximately 94.6% smaller overhead than DDDP and 90.7% smaller than FDDDP, because of statically configured amount credit CBDDP delivers on average 7.5 times more of the redundant data packets than DDDP and FDDDP.EAGDDP improves the delivery by 80% on average and makes a balance of energy consumption .We suggest that making these protocols truly self-learning can significantly improve their performance.Comment: 8 pages, 9 figure

Real Time scheduling with Virtual Nodes for Self Stabilization in Wireless Sensor Networks

In this paper we propose a new scheduling algorithm called Real Time Scheduling (RTS) which uses virtual nodes for self stabilization. This algorithm deals with all the contributing components of the end-to-end travelling delay of data packets in sensor network and with virtual nodes algorithm achieves QoS in terms of packet delivery, multiple connections, better power management and stable routes in case of failure. RTS delays packets at intermediate hops (not just prioritizes them) for a duration that is a function of their deadline. Delaying packets allows the network to avoid hot spotting while maintaining deadline-faithfulness. We compare RTS with another prioritizing and scheduling algorithm for real-time data dissemination in sensor networks, velocity monotonic scheduling. This paper simulates RTS based on two typical routing protocols, shortest path routing and greedy forwarding with J-Sim.Comment: arXiv admin note: substantial text overlap with arXiv:cs/0608069 by other authors without attributio

Decentralized Lifetime Minimizing Tree for Data Aggregation in Wireless Sensor Networks

To meet the demands of wireless sensor networks (WSNs) where data are usually aggregated at a single source prior to transmitting to any distant user, there is a need to establish a tree structure inside any given event region. In this paper, we propose a novel technique to create one such tree, which preserves the energy and minimizes the lifetime of event sources while they are constantly transmitting for data aggregation in future WSNs. We use the term Decentralized Lifetime-Minimizing Tree (DLMT) to denote this tree. DLMT features in nodes with higher energy tend to be chosen as data aggregating parents so that the time to detect the first broken tree link can be extended and less energy is involved in tree maintenance. In addition, by constructing the tree in such a way, the protocol is also able to reduce the frequency of tree reconstruction, minimizes the amount of data loss, minimizes the delay during data collection and preserves the energy. Forwarded directed Diffusion protocol is chosen as the routing platform.Comment: 12 pages, 4 figure

Decentralized Lifetime Maximizing Tree with Clustering for Data Delivery in Wireless Sensor Networks

A wireless sensor network has a wide application domain which is expanding everyday and they have been deployed pertaining to their application area. An application independent approach is yet to come to terms with the ongoing exploitation of the WSNs. In this paper we propose a decentralized lifetime maximizing tree for application independent data aggregation scheme using the clustering for data delivery in WSNs. The proposed tree will minimize the energy consumption which has been a resisting factor in the smooth working of WSNs as well as minimize the distance between the communicating nodes under the control of a sub-sink which further communicate and transfer data to the sink node.Comment: 9 pages, 8 figure

Performance Comparison of Proposed Lifetime Maximizing Trees for Data Aggregation in Wireless Sensor Networks

In this paper a packet level simulator is used to explore the performance of the proposed DLMT and CLMT algorithms under various traffic conditions. Performance of the proposed algorithms is compared with already existing E-Span tree structure. These proposed algorithms tend to extend the node lifetime in order to increase the amount of information gathered by the tree root. Decentralized lifetime maximizing tree (DLMT) features in nodes with higher energy to be chosen as data aggregating parents while Centralized Lifetime Maximizing Tree (CLMT) features with the identification of the bottleneck node to collect data in a central manner among given set of nodes. By choosing Forwarded Diffusion as our underlying routing platform the simulations are carried on J-Sim. Our simulation results have shown that the functional lifetime of event sources can be enhanced by a maximum of 147% when data is aggregated via DLMT and by 139% when data is aggregated via CLMT. Our proposed DLMT algorithm has shown maximum of 13% additional lifetime saving without increasing the delay. Packet delivery ratio has also shown a remarkable increase when the tree depth is considered in these proposed tree structures. Furthermore, the delay is also reduced by using DLMT & CLMT in comparison with E-Span.Comment: 13 pages, 8 figures; International Journal on Computer Science and Engineering (IJCSE)Volume 3 Issue 1 201

Stable Routing for achieving Quality of Service in wireless Sensor Networks

Networking in Wireless Sensor networks is a challenging task due to the lack of resources in the network as well as the frequent changes in network topology. Although lots of research has been done on supporting QoS in the Internet and other networks, but they are not suitable for wireless sensor networks and still QoS support for such networks remains an open problem. In this paper, a new scheme has been proposed for achieving QoS in terms of packet delivery, multiple connections, better power management and stable routes in case of failure. It offers quick adaptation to distributed processing, dynamic linking, low processing overhead and loop freedom at all times. The proposed scheme has been incorporated using QDPRA protocol and by extensive simulation the performance has been studied, and it is clearly shown that the proposed scheme performs very well for different network scenarios.Comment: 7 pages,6 figures; IJCA Special Issue on MANETs, 201

Hierarchical Reinforcement Learning for Quadruped Locomotion

Legged locomotion is a challenging task for learning algorithms, especially when the task requires a diverse set of primitive behaviors. To solve these problems, we introduce a hierarchical framework to automatically decompose complex locomotion tasks. A high-level policy issues commands in a latent space and also selects for how long the low-level policy will execute the latent command. Concurrently, the low-level policy uses the latent command and only the robot's on-board sensors to control the robot's actuators. Our approach allows the high-level policy to run at a lower frequency than the low-level one. We test our framework on a path-following task for a dynamic quadruped robot and we show that steering behaviors automatically emerge in the latent command space as low-level skills are needed for this task. We then show efficient adaptation of the trained policy to a different task by transfer of the trained low-level policy. Finally, we validate the policies on a real quadruped robot. To the best of our knowledge, this is the first application of end-to-end hierarchical learning to a real robotic locomotion task

A Novel Framework for Intelligent Information Retrieval in Wireless Sensor Networks

Recent advances in the development of the low-cost, power-efficient embedded devices, coupled with the rising need for support of new information processing paradigms such as smart spaces and military surveillance systems, have led to active research in large-scale, highly distributed sensor networks of small, wireless, low-power, unattended sensors and actuators. While applications keep diversifying, one common property they share is the need for an efficient network architecture tailored towards information retrieval in sensor networks. Previous solutions designed for traditional networks serve as good references; however, due to the vast differences between previous paradigms and needs of sensor networks, a framework is required to gather and impart only the required information .To achieve this goal in this paper we have proposed a framework for intelligent information retrieval and dissemination to desired destination node. The proposed frame work combines three major concern areas in WSNs i.e. data aggregation, information retrieval and data dissemination in a single scenario. In the proposed framework data aggregation is responsible for combining information from all nodes and removing the redundant data. Information retrieval filters the processed data to obtain final information termed as intelligent data to be disseminated to the required destination node.Comment: 5 pages, 4 figures; ERCICA 2014 - Emerging Research in Computing, Information, Communication and Applications (Vol 2), Elsevier Science and Technolog