Sensor networks arise as one of the most promising technologies for the next decades. The recent emergence of small and inexpensive sensors based upon microelectromechanical system (MEMS) ease the development and proliferation of this kind of networks in a wide range of real-world applications. MultiAgent systems (MAS) have been identified as one of the most suitable technologies to contribute to this domain due to their appropriateness for modeling autonomous self-aware sensors in a flexible way. Firstly, this survey summarizes the actual challenges and research areas concerning sensor networks while identifying the most relevant MAS contributions. Secondly, we propose a taxonomy for sensor networks that classifies them depending on their features (and the research problems they pose). Finally, we identify some open future research directions and opportunities for MAS research.

In this paper we propose a novel message-passing algorithm, the so-called Action-GDL, as an extension to the generalized distributive law (GDL) to efficiently solve DCOPs. Action-GDL provides a unifying perspective of several dynamic programming DCOP algorithms that are based on GDL, such as DPOP and DCPOP algorithms. We empirically show how Action-GDL using a novel distributed post-processing heuristic can outperform DCPOP, and by extension DPOP, even when the latter uses the best arrangement provided by multiple state-of-the-art heuristics.

Matching demand and supply is recognized as a crucial issue for smart grids, and ICT-based solutions are essential to deliver the infrastructure, algorithms and mechanisms for demand-supply balancing. To date, most work in this area focus on providing users with real time feedback on energy prices and consumption, or on load scheduling of home appliances for individual user consumption. In this paper, we take a complementary approach by exploiting social relationships among consumers to organise them into coalitions of Virtual Electricity Consumers (VECs) that buy electricity as a single customer in order to get a discount on electricity through collective buying. Specifically, we model our problem as a coalitional game and provide an algorithm, based on linear programming, to form VECs. The VECs formed by our algorithm are both efficient (i.e., minimizing the sum of users' payments) and stable (i.e., no user has any incentive to break away). We empirically analyse our approach using real consumption data for a set of households located in UK. Our analysis provides interesting insights into the relationship between structure and stability of VEC's and prices within the electricity market.

Power distribution network management must integrate with demand side management, alongside distributed energy resources, in order to meet sustainability, resilience, and economic challenges through a smart grid approach. This paper presents an implementation of the Universal Smart Energy Framework (USEF) through a multiagent system and a novel semantic web ontology, which aligns and enriches relevant existing standards. USEF provides a common specification of the market processes and information exchange but does not specify the internal reasoning of the different roles involved. The authors explain the systematic design and development process from the requirements of the energy-flexibility value chain to software implementation. The underpinning ontology formalizes a domain perspective which is coherent with existing standards, and is sufficient for the agent-oriented implementation of the mentioned framework. As well as contributing this model as a web ontology artifact, the presented work utilizes metaprogramming to transform the domain model into a standard agent communication language ontology. The research reported in this paper is expected to lead towards efficient and scalable development of decision support and automation software for smart grids.