1,706 research outputs found
Positioning and Scheduling of Wireless Sensor Networks - Models, Complexity, and Scalable Algorithms
Improving IF Algorithm for Data Aggregation Techniques in Wireless Sensor Networks
In Wireless Sensor Network (WSN), fact from different sensor nodes is collected at assembling node, which is typically complete via modest procedures such as averaging as inadequate computational power and energy resources. Though such collections is identified to be extremely susceptible to node compromising attacks. These approaches are extremely prone to attacks as WSN are typically lacking interfere resilient hardware. Thus, purpose of veracity of facts and prestige of sensor nodes is critical for wireless sensor networks. Therefore, imminent gatherer nodes will be proficient of accomplishment additional cultivated data aggregation algorithms, so creating WSN little unresisting, as the performance of actual low power processors affectedly increases. Iterative filtering algorithms embrace inordinate capacity for such a resolution. The way of allocated the matching mass elements to information delivered by each source, such iterative algorithms concurrently assemble facts from several roots and deliver entrust valuation of these roots. Though suggestively extra substantial against collusion attacks beside the modest averaging techniques, are quiet vulnerable to a different cultivated attack familiarize. The existing literature is surveyed in this paper to have a study of iterative filtering techniques and a detailed comparison is provided. At the end of this paper new technique of improved iterative filtering is proposed with the help of literature survey and drawbacks found in the literature
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
Performance Review of Selected Topology-Aware Routing Strategies for Clustering Sensor Networks
In this paper, cluster-based routing (CBR) protocols for addressing issues pertinent to energy consumption, network lifespan, resource allocation and network coverage are reviewed. The paper presents an indepth performance analysis and critical review of selected CBR algorithms. The study is domain-specific and simulation-based with emphasis on the tripartite trade-off between coverage, connectivity and lifespan. The rigorous statistical analysis of selected CBR schemes was also presented. Network simulation was conducted with Java-based Atarraya discrete-event simulation toolkit while statistical analysis was carried out using MATLAB. It was observed that the Periodic, Event-Driven and Query-Based Routing (PEQ) schemes performs better than Low-Energy Adaptive Clustering Hierarchy (LEACH), Threshold-Sensitive Energy-Efficient Sensor Network (TEEN) and Geographic Adaptive Fidelity (GAF) in terms of network lifespan, energy consumption and network throughput.Keywords: Wireless sensor network, Hierarchical topologies, Cluster-based routing, Statistical analysis, Network simulatio
Robotic Wireless Sensor Networks
In this chapter, we present a literature survey of an emerging, cutting-edge,
and multi-disciplinary field of research at the intersection of Robotics and
Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor
Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system
that aims to achieve certain sensing goals while meeting and maintaining
certain communication performance requirements, through cooperative control,
learning and adaptation. While both of the component areas, i.e., Robotics and
WSN, are very well-known and well-explored, there exist a whole set of new
opportunities and research directions at the intersection of these two fields
which are relatively or even completely unexplored. One such example would be
the use of a set of robotic routers to set up a temporary communication path
between a sender and a receiver that uses the controlled mobility to the
advantage of packet routing. We find that there exist only a limited number of
articles to be directly categorized as RWSN related works whereas there exist a
range of articles in the robotics and the WSN literature that are also relevant
to this new field of research. To connect the dots, we first identify the core
problems and research trends related to RWSN such as connectivity,
localization, routing, and robust flow of information. Next, we classify the
existing research on RWSN as well as the relevant state-of-the-arts from
robotics and WSN community according to the problems and trends identified in
the first step. Lastly, we analyze what is missing in the existing literature,
and identify topics that require more research attention in the future
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