10,582 research outputs found
Deadline-Aware Energy-Efficient Query Scheduling in Wireless Sensor Networks with Mobile Sink
Mobile sinks are proposed to save sensor energy spent for multihop communication in transferring data to a base station (sink) in Wireless Sensor Networks. Due to relative low speed of mobile sinks, these approaches are mostly suitable for delay-tolerant applications. In this paper, we study the design of a query scheduling algorithm for query-based data gathering applications using mobile sinks. However, these kinds of applications are sensitive to delays due to specified query deadlines. Thus, the proposed scheduling algorithm aims to minimize the number of missed deadlines while keeping the level of energy consumption at the minimum
Delay Sensive Routing In Three Dimensional Underwater Acoustic Sensor Networks
Recent improvements in wireless communications and acoustic technology have enabled the use of sensor networks in underwater environments. Under-water sensor network is an emerging field which requires research in the field of channel access and routing. Some applications such as disaster prevention, assisted navigation and tactical surveillance require minimum delay in data-gathering. The routing algorithm proposed in this work for delay-sensitive applications uses a distributed approach. Each node in the proposed distributed rouging chooses its next hop. A local path repair algorithm is used to repair the links in a distributed manner. It enables faster recovery of node failure and link failure which increases the data-gathering rate. The best next hop is chosen to minimize delay, retransmissions of the packet already transmitted, idle source time and energy expenditure. Through simulations, the proposed algorithm is shown to achieve a better performance in data-gathering when compared to a centralized scheme.Computer Science Departmen
LPTA: Location predictive and time adaptive data gathering scheme with mobile sink for wireless sensor networks
This paper exploits sink mobility to prolong the lifetime of sensor networks while maintaining the data transmission delay relatively low. A location predictive and time adaptive data gathering scheme is proposed. In this paper, we introduce a sink location prediction principle based on loose time synchronization and deduce the time-location formulas of the mobile sink. According to local clocks and the time-location formulas of the mobile sink, nodes in the network are able to calculate the current location of the mobile sink accurately and route data packets timely toward the mobile sink by multihop relay. Considering that data packets generating from different areas may be different greatly, an adaptive dwelling time adjustment method is also proposed to balance energy consumption among nodes in the network. Simulation results show that our data gathering scheme enables data routing with less data transmission time delay and balance energy consumption among nodes.The work is supported by the Science and Technology Pillar Program of Changzhou (Social Development), no. CE20135052. Joel J. P. C. Rodrigues's work has been supported by the Fundamental Research Funds for the Central Universities (Program no. HEUCF140803), by Instituto de Telecomunicacoes, Next Generation Networks and Applications Group (NetGNA), Covilha Delegation, by Government of Russian Federation, Grant 074-U01, and by National Funding from the FCT-Fundacao para a Ciencia e a Tecnologia through the Pest-OE/EEI/LA0008/2013 Project.Zhu, C.; Wang, Y.; Han, G.; Rodrigues, JJPC.; Lloret, J. (2014). LPTA: Location predictive and time adaptive data gathering scheme with mobile sink for wireless sensor networks. Scientific World Journal. https://doi.org/10.1155/2014/476253SHan, G., Xu, H., Jiang, J., Shu, L., Hara, T., & Nishio, S. (2011). Path planning using a mobile anchor node based on trilateration in wireless sensor networks. Wireless Communications and Mobile Computing, 13(14), 1324-1336. doi:10.1002/wcm.1192Zhu, C., Zheng, C., Shu, L., & Han, G. (2012). A survey on coverage and connectivity issues in wireless sensor networks. Journal of Network and Computer Applications, 35(2), 619-632. doi:10.1016/j.jnca.2011.11.016Han, G., Xu, H., Duong, T. Q., Jiang, J., & Hara, T. (2011). Localization algorithms of Wireless Sensor Networks: a survey. Telecommunication Systems, 52(4), 2419-2436. doi:10.1007/s11235-011-9564-7Guoliang Xing, Tian Wang, Zhihui Xie, & Weijia Jia. (2008). Rendezvous Planning in Wireless Sensor Networks with Mobile Elements. IEEE Transactions on Mobile Computing, 7(12), 1430-1443. doi:10.1109/tmc.2008.58Basagni, S., Carosi, A., Melachrinoudis, E., Petrioli, C., & Wang, Z. M. (2007). Controlled sink mobility for prolonging wireless sensor networks lifetime. Wireless Networks, 14(6), 831-858. doi:10.1007/s11276-007-0017-xWang, G., Wang, T., Jia, W., Guo, M., & Li, J. (2008). Adaptive location updates for mobile sinks in wireless sensor networks. The Journal of Supercomputing, 47(2), 127-145. doi:10.1007/s11227-008-0181-5Shin, K., & Kim, S. (2012). Predictive routing for mobile sinks in wireless sensor networks: a milestone-based approach. The Journal of Supercomputing, 62(3), 1519-1536. doi:10.1007/s11227-012-0815-5Lee, K., Kim, Y.-H., Kim, H.-J., & Han, S. (2013). A myopic mobile sink migration strategy for maximizing lifetime of wireless sensor networks. Wireless Networks, 20(2), 303-318. doi:10.1007/s11276-013-0606-9Sheu, J.-P., Sahoo, P. K., Su, C.-H., & Hu, W.-K. (2010). Efficient path planning and data gathering protocols for the wireless sensor network. Computer Communications, 33(3), 398-408. doi:10.1016/j.comcom.2009.10.011Yang, Y., Fonoage, M. I., & Cardei, M. (2010). Improving network lifetime with mobile wireless sensor networks. Computer Communications, 33(4), 409-419. doi:10.1016/j.comcom.2009.11.010Liang, W., Luo, J., & Xu, X. (2011). Network lifetime maximization for time-sensitive data gathering in wireless sensor networks with a mobile sink. Wireless Communications and Mobile Computing, 13(14), 1263-1280. doi:10.1002/wcm.1179Kinalis, A., Nikoletseas, S., Patroumpa, D., & Rolim, J. (2014). Biased sink mobility with adaptive stop times for low latency data collection in sensor networks. Information Fusion, 15, 56-63. doi:10.1016/j.inffus.2012.04.003Liu, C. H., Ssu, K. F., & Wang, W. T. (2011). A moving algorithm for non-uniform deployment in mobile sensor networks. International Journal of Autonomous and Adaptive Communications Systems, 4(3), 271. doi:10.1504/ijaacs.2011.040987Shi, L., Zhang, B., Mouftah, H. T., & Ma, J. (2012). DDRP: An efficient data-driven routing protocol for wireless sensor networks with mobile sinks. International Journal of Communication Systems, n/a-n/a. doi:10.1002/dac.2315Liu, X., Zhao, H., Yang, X., & Li, X. (2013). SinkTrail: A Proactive Data Reporting Protocol for Wireless Sensor Networks. IEEE Transactions on Computers, 62(1), 151-162. doi:10.1109/tc.2011.207Aioffi, W. M., Valle, C. A., Mateus, G. R., & da Cunha, A. S. (2011). Balancing message delivery latency and network lifetime through an integrated model for clustering and routing in Wireless Sensor Networks. Computer Networks, 55(13), 2803-2820. doi:10.1016/j.comnet.2011.05.023Liu, D., Zhang, K., & Ding, J. (2013). Energy-efficient transmission scheme for mobile data gathering in Wireless Sensor Networks. China Communications, 10(3), 114-123. doi:10.1109/cc.2013.648883
Optimal coverage multi-path scheduling scheme with multiple mobile sinks for WSNs
Wireless Sensor Networks (WSNs) are usually formed with many tiny sensors which are randomly deployed within sensing field for target monitoring. These sensors can transmit their monitored data to the sink in a multi-hop communication manner. However, the âhot spotsâ problem will be caused since nodes near sink will consume more energy during forwarding. Recently, mobile sink based technology provides an alternative solution for the long-distance communication and sensor nodes only need to use single hop communication to the mobile sink during data transmission. Even though it is difficult to consider many network metrics such as sensor position, residual energy and coverage rate etc., it is still very important to schedule a reasonable moving trajectory for the mobile sink. In this paper, a novel trajectory scheduling method based on coverage rate for multiple mobile sinks (TSCR-M) is presented especially for large-scale WSNs. An improved particle swarm optimization (PSO) combined with mutation operator is introduced to search the parking positions with optimal coverage rate. Then the genetic algorithm (GA) is adopted to schedule the moving trajectory for multiple mobile sinks. Extensive simulations are performed to validate the performance of our proposed method
EMEEDP: Enhanced Multi-hop Energy Efficient Distributed Protocol for Heterogeneous Wireless Sensor Network
In WSN (Wireless Sensor Network) every sensor node sensed the data and
transmit it to the CH (Cluster head) or BS (Base Station). Sensors are randomly
deployed in unreachable areas, where battery replacement or battery charge is
not possible. For this reason, Energy conservation is the important design goal
while developing a routing and distributed protocol to increase the lifetime of
WSN. In this paper, an enhanced energy efficient distributed protocol for
heterogeneous WSN have been reported. EMEEDP is proposed for heterogeneous WSN
to increase the lifetime of the network. An efficient algorithm is proposed in
the form of flowchart and based on various clustering equation proved that the
proposed work accomplishes longer lifetime with improved QOS parameters
parallel to MEEP. A WSN implemented and tested using Raspberry Pi devices as a
base station, temperature sensors as a node and xively.com as a cloud. Users
use data for decision purpose or business purposes from xively.com using
internet.Comment: 6 pages, 4 figures. arXiv admin note: substantial text overlap with
arXiv:1409.1412 by other author
Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey
Wireless sensor networks (WSNs) consist of autonomous and resource-limited
devices. The devices cooperate to monitor one or more physical phenomena within
an area of interest. WSNs operate as stochastic systems because of randomness
in the monitored environments. For long service time and low maintenance cost,
WSNs require adaptive and robust methods to address data exchange, topology
formulation, resource and power optimization, sensing coverage and object
detection, and security challenges. In these problems, sensor nodes are to make
optimized decisions from a set of accessible strategies to achieve design
goals. This survey reviews numerous applications of the Markov decision process
(MDP) framework, a powerful decision-making tool to develop adaptive algorithms
and protocols for WSNs. Furthermore, various solution methods are discussed and
compared to serve as a guide for using MDPs in WSNs
AM-DisCNT: Angular Multi-hop DIStance based Circular Network Transmission Protocol for WSNs
The nodes in wireless sensor networks (WSNs) contain limited energy
resources, which are needed to transmit data to base station (BS). Routing
protocols are designed to reduce the energy consumption. Clustering algorithms
are best in this aspect. Such clustering algorithms increase the stability and
lifetime of the network. However, every routing protocol is not suitable for
heterogeneous environments. AM-DisCNT is proposed and evaluated as a new energy
efficient protocol for wireless sensor networks. AM-DisCNT uses circular
deployment for even consumption of energy in entire wireless sensor network.
Cluster-head selection is on the basis of energy. Highest energy node becomes
CH for that round. Energy is again compared in the next round to check the
highest energy node of that round. The simulation results show that AM-DisCNT
performs better than the existing heterogeneous protocols on the basis of
network lifetime, throughput and stability of the system.Comment: IEEE 8th International Conference on Broadband and Wireless
Computing, Communication and Applications (BWCCA'13), Compiegne, Franc
Joint Routing and STDMA-based Scheduling to Minimize Delays in Grid Wireless Sensor Networks
In this report, we study the issue of delay optimization and energy
efficiency in grid wireless sensor networks (WSNs). We focus on STDMA (Spatial
Reuse TDMA)) scheduling, where a predefined cycle is repeated, and where each
node has fixed transmission opportunities during specific slots (defined by
colors). We assume a STDMA algorithm that takes advantage of the regularity of
grid topology to also provide a spatially periodic coloring ("tiling" of the
same color pattern). In this setting, the key challenges are: 1) minimizing the
average routing delay by ordering the slots in the cycle 2) being energy
efficient. Our work follows two directions: first, the baseline performance is
evaluated when nothing specific is done and the colors are randomly ordered in
the STDMA cycle. Then, we propose a solution, ORCHID that deliberately
constructs an efficient STDMA schedule. It proceeds in two steps. In the first
step, ORCHID starts form a colored grid and builds a hierarchical routing based
on these colors. In the second step, ORCHID builds a color ordering, by
considering jointly both routing and scheduling so as to ensure that any node
will reach a sink in a single STDMA cycle. We study the performance of these
solutions by means of simulations and modeling. Results show the excellent
performance of ORCHID in terms of delays and energy compared to a shortest path
routing that uses the delay as a heuristic. We also present the adaptation of
ORCHID to general networks under the SINR interference model
Traffic eavesdropping based scheme to deliver time-sensitive data in sensor networks
Due to the broadcast nature of wireless channels, neighbouring sensor nodes may overhear packets transmissions from each other even if they are not the intended recipients of these transmissions. This redundant packet reception leads to unnecessary expenditure of battery energy of the recipients. Particularly in highly dense sensor networks, overhearing or eavesdropping overheads can constitute a significant fraction of the total energy consumption. Since overhearing of wireless traffic is unavoidable and sometimes essential, a new distributed energy efficient scheme is proposed in this paper. This new scheme exploits the inevitable overhearing effect as an effective approach in order to collect the required information to perform energy efficient delivery for data aggregation. Based on this approach, the proposed scheme achieves moderate energy consumption and high packet delivery rate notwithstanding the occurrence of high link failure rates. The performance of the proposed scheme is experimentally investigated a testbed of TelosB motes in addition to ns-2 simulations to validate the performed experiments on large-scale network
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