In this Chapter, we imagine a decision maker (or a group of experts) trying to establish or examine fair procedures to combine opinions about alternatives related to different points of view.

Multiple criteria decision making

Lecture Notes in Economics and Mathematical Systems

We survey recent advances in algorithms for route planning in transportation networks. For road networks, we show that one can compute driving directions in milliseconds or less even at continental scale. A variety of techniques provide different trade-offs between preprocessing effort, space requirements, and query time. Some algorithms can answer queries in a fraction of a microsecond, while others can deal efficiently with real-time traffic. Journey planning on public transportation systems, although conceptually similar, is a significantly harder problem due to its inherent time-dependent and multicriteria nature. Although exact algorithms are fast enough for interactive queries on metropolitan transit systems, dealing with continent-sized instances requires simplifications or heavy preprocessing. The multimodal route planning problem, which seeks journeys combining schedule-based transportation (buses, trains) with unrestricted modes (walking, driving), is even harder, relying on approximate solutions even for metropolitan inputs.

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Route Planning in Transportation Networks

We present a new tweakable block cipher family SKINNY, whose goal is to compete with NSA recent design SIMON in terms of hardware/software performances, while proving in addition much stronger security guarantees with regards to differential/linear attacks. In particular, unlike SIMON, we are able to provide strong bounds for all versions, and not only in the single-key model, but also in the related-key or related-tweak model. SKINNY has flexible block/key/tweak sizes and can also benefit from very efficient threshold implementations for side-channel protection. Regarding performances, it outperforms all known ciphers for ASIC round-based implementations, while still reaching an extremely small area for serial implementations and a very good efficiency for software and micro-controllers implementations SKINNY has the smallest total number of AND/OR/XOR gates used for encryption process.

Secondly, we present MANTIS, a dedicated variant of SKINNY for low-latency implementations, that constitutes a very efficient solution to the problem of designing a tweakable block cipher for memory encryption. MANTIS basically reuses well understood, previously studied, known components. Yet, by putting those components together in a new fashion, we obtain a competitive cipher to PRINCE in latency and area, while being enhanced with a tweak input.

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The SKINNY Family of Block Ciphers and Its Low-Latency Variant MANTIS

Swarm intelligence (SI) algorithms, including ant colony optimization, particle swarm optimization, bee-inspired algorithms, bacterial foraging optimization, firefly algorithms, fish swarm optimization and many more, have been proven to be good methods to address difficult optimization problems under stationary environments. Most SI algorithms have been developed to address stationary optimization problems and hence, they can converge on the (near-) optimum solution efficiently. However, many real-world problems have a dynamic environment that changes over time. For such dynamic optimization problems (DOPs), it is difficult for a conventional SI algorithm to track the changing optimum once the algorithm has converged on a solution. In the last two decades, there has been a growing interest of addressing DOPs using SI algorithms due to their adaptation capabilities. This paper presents a broad review on SI dynamic optimization (SIDO) focused on several classes of problems, such as discrete, continuous, constrained, multi-objective and classification problems, and real-world applications. In addition, this paper focuses on the enhancement strategies integrated in SI algorithms to address dynamic changes, the performance measurements and benchmark generators used in SIDO. Finally, some considerations about future directions in the subject are given.

A survey of swarm intelligence for dynamic optimization: Algorithms and applications

Quality of service (QoS) can be a critical element for achieving the business goals of a service provider, for the acceptance of a service by the user, or for guaranteeing service characteristics in a composition of services, where a service is defined as either a software or a software-support (i.e., infrastructural) service which is available on any type of network or electronic channel. The goal of this article is to compare the approaches to QoS description in the literature, where several models and metamodels are included. consider a large spectrum of models and metamodels to describe service quality, ranging from ontological approaches to define quality measures, metrics, and dimensions, to metamodels enabling the specification of quality-based service requirements and capabilities as well as of SLAs (Service-Level Agreements) and SLA templates for service provisioning. Our survey is performed by inspecting the characteristics of the available approaches to reveal which are the consolidated ones and which are the ones specific to given aspects and to analyze where the need for further research and investigation lies. The approaches here illustrated have been selected based on a systematic review of conference proceedings and journals spanning various research areas in computer science and engineering, including: distributed, information, and telecommunication systems, networks and security, and service-oriented and grid computing.

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Salima Benrernou

Papers

A survey on service quality description