Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial

Energy Market Integration in East Asia: A Regional Public Goods Approach

This study applies a regional public goods approach to the study of energy market integration (EMI) in East Asia, with a view to clarifying the outlook for such integration and the likely obstacles to be encountered. In addition to drawing on theoretical ideas relating to regional public goods, the paper will also draw on the experience of the European Union in its attempts to develop a single energy market. The study shows that many services are needed in order to develop and sustain a regional integrated energy market and that some of these services have characteristics of regional public goods, though some may also be trans-regional or global in nature as well. The study recommends that: EMI in East Asia should be pursued in an incremental manner and mainly at a sub-regional scale; and the specific steps taken towards EMI should be chosen on the basis of their likely positive economic impacts and their likely ease of delivery.