By Sharief M. A. Oteafy, Hossam S. Hassanein
In this name, the authors bounce right into a novel paradigm of scalability and cost-effectiveness, at the foundation of source reuse. In a global with a lot abundance of wirelessly available units, WSN deployments should still capitalize at the assets already on hand within the sector of deployment, and purely increase it with the elements required to fulfill new software standards. besides the fact that, if the mandatory assets exist already in that zone, WSN deployment converges to an task and scheduling scheme to deal with for the recent program given the prevailing assets. Such assets are polled from many fields, together with a number of WSNs already within the box, static networks (WiFi, WiMAX, mobile, and so forth) as well as municipal, commercial and cellular resources.The structure, framework and pricing coverage, in addition to methods for backward compatibility with latest deployments, are offered during this booklet. We intricate at the formalization of the matter, and distinction with present paintings on assurance. This paradigm adopts optimum assignments in WSNs and exploits dynamic re-programming for enhancing post-deployment and backward appropriate protocols.
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Additional resources for Dynamic Wireless Sensor Networks
2. g. query) to be met. In WSNs, the duty cycling of sensing nodes, the control overhead, MAC contention and back-off timers, in addition to sensing latency, all prolong WSN responsiveness. Thus, integrating a system that is mostly assumed to be eventtriggered or low-duty-cycled with a system that is responsive by design will create significant discrepancies.
Exploiting Sink Mobility for Maximizing Sensor Networks Lifetime”, System Sciences, 2005. HICSS '05. Proceedings of the 38th Annual Hawaii International Conference on , vol. 287a, 287a, 03–06 Jan. , “Sensor relocation in mobile sensor networks”, Proceedings of IEEE Annual Joint Conference of the IEEE Computer and Communications Societies, (INFOCOM), vol. 4, pp. 2302–2312, 2005. , “Topology management techniques for tolerating node failure”, The Art of Wireless Sensor Networks, Springer Berlin Heidelberg, pp.
1. The cloud variants The cloud evolved as a virtual resource pool that exists on the Internet, manifesting hardware that resides over different geographical locations. The spatial distribution of these locations, and the rules of shared resources, along with the access rights given to different users, dictated a differentiation in the types of clouds. We elaborate on three distinct types of clouds. The first is the Private Cloud which serves a given company/deployment. It offers a dedicated virtualization of resources to terminals belonging to a company, for example, and eases maintenance and software upgrades that are to impact cloud-connected terminals.
Dynamic Wireless Sensor Networks by Sharief M. A. Oteafy, Hossam S. Hassanein