Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs

Applying Real Options Thinking to Information Security in Networked Organizations

An information security strategy of an organization participating in a networked business sets out the plans for designing a variety of actions that ensure confidentiality, availability, and integrity of company’s key information assets. The actions are concerned with authentication and nonrepudiation of authorized users of these assets. We assume that the primary objective of security efforts in a company is improving and sustaining resiliency, which means security contributes to the ability of an organization to withstand discontinuities and disruptive events, to get back to its normal operating state, and to adapt to ever changing risk environments. When companies collaborating in a value web view security as a business issue, risk assessment and cost-benefit analysis techniques are necessary and explicit part of their process of resource allocation and budgeting, no matter if security spendings are treated as capital investment or operating expenditures. This paper contributes to the application of quantitative approaches to assessing risks, costs, and benefits associated with the various components making up the security strategy of a company participating in value networks. We take a risk-based approach to determining what types of security a strategy should include and how much of each type is enough. We adopt a real-options-based perspective of security and make a proposal to value the extent to which alternative components in a security strategy contribute to organizational resiliency and protect key information assets from being impeded, disrupted, or destroyed

A Taxonomy for Management and Optimization of Multiple Resources in Edge Computing

Edge computing is promoted to meet increasing performance needs of data-driven services using computational and storage resources close to the end devices, at the edge of the current network. To achieve higher performance in this new paradigm one has to consider how to combine the efficiency of resource usage at all three layers of architecture: end devices, edge devices, and the cloud. While cloud capacity is elastically extendable, end devices and edge devices are to various degrees resource-constrained. Hence, an efficient resource management is essential to make edge computing a reality. In this work, we first present terminology and architectures to characterize current works within the field of edge computing. Then, we review a wide range of recent articles and categorize relevant aspects in terms of 4 perspectives: resource type, resource management objective, resource location, and resource use. This taxonomy and the ensuing analysis is used to identify some gaps in the existing research. Among several research gaps, we found that research is less prevalent on data, storage, and energy as a resource, and less extensive towards the estimation, discovery and sharing objectives. As for resource types, the most well-studied resources are computation and communication resources. Our analysis shows that resource management at the edge requires a deeper understanding of how methods applied at different levels and geared towards different resource types interact. Specifically, the impact of mobility and collaboration schemes requiring incentives are expected to be different in edge architectures compared to the classic cloud solutions. Finally, we find that fewer works are dedicated to the study of non-functional properties or to quantifying the footprint of resource management techniques, including edge-specific means of migrating data and services.Comment: Accepted in the Special Issue Mobile Edge Computing of the Wireless Communications and Mobile Computing journa