Abstract
WSNs as adopted in current smart city deployments, must address demanding traffic factors and resilience in failures. Furthermore, caching of data in WSN can significantly benefit resource conservation and network performance. However, data sources generate data volumes that could not fit in the restricted data cache resources of the caching nodes. This unavoidably leads to data items been evicted and replaced. This paper aims to experimentally evaluate the prominent caching techniques in large scale networks that resemble the Smart city paradigm regarding network performance with respect to critical application and network parameters. Through respective result analysis valuable insights are provided concerning the behaviour of caching in typical large scale WSN scenarios.
Highlights
During the last several years Smart Cities concept is attracting active interest as a prominent approach to enhance everyday life quality
At the same time advancements in VLSI and embedded systems allow for sensors to be miniaturized able to be embedded in almost any device, a car, a lamppost or even been worn by individuals effectively making them part of the Smart City network [5]
The respective significant benefits cache techniques can yield relative limited effort is available concerning the effect of applying such techniques in large scale networks, networking driven cache functionalities as well as strategic placement of cache to maximize the performance enhancement while minimizing the required memory overhead to network nodes
Summary
During the last several years Smart Cities concept is attracting active interest as a prominent approach to enhance everyday life quality. The potential benefits concern a wide range of application scenarios from traffic control and environmental conditions monitoring to individuals' bio signals' monitoring and safety control [1,2,3]. As it is understood such a wide range of different and diverse applications form a quite complex, dynamic and unpredictable set of traffic sources which the underlying networking technology must handle. At the same time advancements in VLSI and embedded systems allow for sensors to be miniaturized able to be embedded in almost any device, a car, a lamppost or even been worn by individuals effectively making them part of the Smart City network [5]
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