Abstract
In sensor-cloud environment, sensing-as-a-service (Sen-aaS) is an emerging service paradigm that allows on-demand provisioning of sensor resources as a service in a pay-per-use model. For each application, a disjoint set of virtual sensors (VS) are consolidated in a collaborative wireless sensor network (WSN) platform distributed across the globe. The virtual sensor network (VSN) of an application, formed using VSs, may span across multiple WSNs and the base station for each of these WSNs are placed in a host on a nearest cloud data center (DC). Here, sensor cloud plays the key role to conglomerate the data from various VSs, store them in different hosts, and transmit the same to end user application as a service (Sen-aaS). In this work, we address the problem of mapping applications on the hosts that conglomerate data from various VSs and transmit it to the end user as a constraint optimization problem. The main motivation is to minimize the maximum data migration time of all applications on sensor cloud while satisfying the host’s load-balancing constraint. We have proposed an algorithm which can solve the problem optimally under certain conditions. For the general case, if the load-balancing constraint is somewhat relaxed, the maximum delay obtained by our algorithm is optimal. When the load-balancing constraint is to be strictly satisfied, the cost of our solution is slightly more than the optimal provided by an Integer Linear Program.
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Sen, B.K., Khatua, S., Das, R.K. (2019). Optimal Mapping of Applications on Data Centers in Sensor-Cloud Environment. In: Chaki, R., Cortesi, A., Saeed, K., Chaki, N. (eds) Advanced Computing and Systems for Security. Advances in Intelligent Systems and Computing, vol 897. Springer, Singapore. https://doi.org/10.1007/978-981-13-3250-0_10
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DOI: https://doi.org/10.1007/978-981-13-3250-0_10
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