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Dynamic wireless mobile framework for distributed collaborative real-time information generation and control systems
Intelligent Transportation Systems (ITS) have only recently discovered the exciting possibilities in the nomadic and ubiquitous computing space to build a new generation of information systems by allowing the vehicle to act both as a carrier and consumer of wireless (and thus omnipresent) information. Wide deployment of such ITS systems may eventually allow for more dynamic and efficient transportation systems, which can contribute in several ways towards greater economic growth whilst respecting environmental sustainability. A great number of researchers have dedicated considerable time and resources to tackling traffic related issues by utilising the new wireless capabilities enabled by ITS; such initiatives cover a wide range of applications such as safety, knowledge sharing and infotainment. Indicative of the extent of such efforts is the plethora of research projects initiated by many national and multi-national organisations such as the EU Framework Programme for Research and Technological Development. To achieve their goals, proposed solutions from such organisations depend on the development and deployment of intelligent wireless mobile communication systems, where data dissemination issues make the prospect of efficient and effective communication a challenging proposition. Presently, Car-to-Car and Car-to-Infrastructure communications are two distinct avenues that make possible efficient and reliable delivery of messages via direct radio links in traffic areas. In all cases, high quality of communication performance is desirable for a communication system composed mostly of roaming participants; such a system needs to be dynamic, flexible and infrastructure-less. Consequently, Mobile Ad hoc Network (MANET)-based networks are a natural fit to ITS
The Wakefield District prolific and priority offender needs analysis and business case: final report
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
Big data analytics for large-scale wireless networks: Challenges and opportunities
© 2019 Association for Computing Machinery. The wide proliferation of various wireless communication systems and wireless devices has led to the arrival of big data era in large-scale wireless networks. Big data of large-scale wireless networks has the key features of wide variety, high volume, real-time velocity, and huge value leading to the unique research challenges that are different from existing computing systems. In this article, we present a survey of the state-of-art big data analytics (BDA) approaches for large-scale wireless networks. In particular, we categorize the life cycle of BDA into four consecutive stages: Data Acquisition, Data Preprocessing, Data Storage, and Data Analytics. We then present a detailed survey of the technical solutions to the challenges in BDA for large-scale wireless networks according to each stage in the life cycle of BDA. Moreover, we discuss the open research issues and outline the future directions in this promising area
Interoperability in a Heterogeneous Team of Search and Rescue Robots
Search and rescue missions are complex operations. A disaster scenario is generally unstructured, time‐varying and unpredictable. This poses several challenges for the successful deployment of unmanned technology. The variety of operational scenarios and tasks lead to the need for multiple robots of different types, domains and sizes. A priori planning of the optimal set of assets to be deployed and the definition of their mission objectives are generally not feasible as information only becomes available during mission. The ICARUS project responds to this challenge by developing a heterogeneous team composed by different and complementary robots, dynamically cooperating as an interoperable team. This chapter describes our approach to multi‐robot interoperability, understood as the ability of multiple robots to operate together, in synergy, enabling multiple teams to share data, intelligence and resources, which is the ultimate objective of ICARUS project. It also includes the analysis of the relevant standardization initiatives in multi‐robot multi‐domain systems, our implementation of an interoperability framework and several examples of multi‐robot cooperation of the ICARUS robots in realistic search and rescue missions
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