Browsing by Subject "Sleep Scheduling"

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Open Access
Energy efficient ip-connectivity with ieee 80211 for home m2m networks
(2014) Özçelik, İhsan Mert
Machine-to-machine communications (M2M) technology enables large-scale communication and networking of devices of various kinds including home devices and appliances. A critical issue for home M2M networks is how to efficiently integrate the already existing home consumer devices and appliances into an IP based wireless M2M network with least modifications to existing components. Due to its popularity and widespread usage in closed spaces, Wi-Fi is a good alternative as a wireless technology to enable M2M networking for home devices. This thesis addresses the energy-efficient integration of home appliances to a Wi-Fi and IP based home M2M network. Towards this goal, we first propose an integration architecture that requires least modifications in existing components. Then, we propose a novel long-term sleep scheduling algorithm to be applied together with the existing 802.11 power save mode (PSM). The proposed scheme utilizes the multicast DNS (mDNS) protocol to maintain device and service availability when devices go into deep sleep mode. We implemented our proposed architecture and algorithm as a prototype to build an M2M network of home appliances as a test-bed. We performed various experiments on this test-bed to evaluate the proper operation and energy savings of our proposal. We also did extensive simulation experiments for larger-scale scenarios. As a result of our test-bed and simulation experiments, we observed energy savings up to 70% compared to the existing infrastructure which applies no sleep mechanism, and up to 20% compared to standard 802.11 PSM scheme, while ensuring device and service availability at the same time.
Open Access
Sleep scheduling for energy conservation in wireless sensor networks with partial coverage
(2006) Yardibi, Tarık
Wireless sensor networks, which consist of many sensor devices communicating with each other in order to sense the environment, is an emerging field in the area of wireless networking. The primary objective in these wireless networks is the efficiency of energy consumption. Since these networks consist of a large number of sensors, allowing some of the nodes to sleep intermittently can greatly increase the network lifetime. Furthermore, some applications do not require 100% coverage of the network field and allowing the coverage to drop below 100%, i.e., partial coverage, can further increase the network lifetime. A sleep scheduling algorithm must be distributed, simple, scalable and energy efficient. In this thesis, the problem of designing such an algorithm which extends network lifetime while maintaining a target level of partial coverage is investigated. An algorithm called Distributed Adaptive Sleep Scheduling Algorithm (DASSA) which does not require location information is proposed. The performance of DASSA is compared with an integer linear programming (ILP) based optimum sleep scheduling algorithm, an oblivious algorithm and with an existing algorithm in the literature. DASSA attains network lifetimes up to 89% of the optimum solution, and it achieves significantly longer lifetimes compared with the other two algorithms. Furthermore, the minimum number of sensors that should be deployed in order to satisfy a given partial coverage target with a certain probability while maintaining connectivity is computed and an ILP formulation is presented for finding the minimum number of sensors that should be activated within the set of deployed sensors.