A greedy approach for resource allocation in Virtual Sensor Networks

Abstract

Abstract-Virtual Sensor Networks (VSNs) envision the creation of general purpose wireless sensor networks which can be easily adapted and configured to support multifold applications with heterogeneous requirements, in contrast with the classical approach of wireless sensor networks vertically optimized on one specific task/service. The very heart of VSNs' vision is the capability to dynamically allocate shared physical resources (processing power, bandwidth, storage) to multiple incoming applications. In this context, we tackle the problem of optimally allocating shared resources in VSNs by proposing an efficient greedy heuristic that aims to maximize the total revenue out of the deployment of multiple concurrent applications while considering the inherent limitations of the shared physical resources. The proposed heuristic is tested on realistic network instances with notable performances in terms of execution time while keeping the gap with respect to the optimal solution limited (below 5%in the tested environments).

Application placement with shared monitoring points in multi-purpose IoT wireless sensor networks

“…Cionca et al [20] propose Judishare, a framework that enables the reuse of sensing and communication resources in shared sensor networks. In [21], Bousnina et al focus on the resource allocation problem in a virtual sensor network that has sensor nodes with various amounts of resources. They propose a greedy approach to solve the problem.…”

Cloud Based IoT Network Virtualization for Supporting Dynamic Connectivity among Connected Devices

“…The Things Network provides a set of tools that are more focused on rapid IoT application development with minimal/zero coding efforts through drag and drop operations [17]. Efficient resource allocation in the virtual sensor network environment is a challenging problem, and various solutions are proposed in the literature to address this issue [18][19][20][21]. The concept of virtualization in WSN is not new [22][23][24].…”

Load‐Balancing and QoS Based Dynamic Resource Allocation Method for Smart Gird Fiber‐Wireless Networks

“…For static embedding mechanism, Refs. [8][9][10][11][12] respectively used time division multiplexing, frequency division multiplexing and space division multiplexing technology to allocate different time slots, spectrums and spaces for different virtual networks.For smart grid communication networks, a wireless network virtual mapping algorithm based on particle swarm optimization is proposed [13] . It could guarantee the real-time reliability of business and maximize the throughput of the business.…”