447 research outputs found
Cloud Computing Strategies for Enhancing Smart Grid Performance in Developing Countries
In developing countries, the awareness and development of Smart Grids are in the introductory stage and the full realisation needs more time and effort. Besides, the partially introduced Smart Grids are inefficient, unreliable, and environmentally unfriendly. As the global economy crucially depends on energy sustainability, there is a requirement to revamp the existing energy systems. Hence, this research work aims at cost-effective optimisation and communication strategies for enhancing Smart Grid performance on Cloud platforms
Mobile Edge Computing
This is an open access book. It offers comprehensive, self-contained knowledge on Mobile Edge Computing (MEC), which is a very promising technology for achieving intelligence in the next-generation wireless communications and computing networks. The book starts with the basic concepts, key techniques and network architectures of MEC. Then, we present the wide applications of MEC, including edge caching, 6G networks, Internet of Vehicles, and UAVs. In the last part, we present new opportunities when MEC meets blockchain, Artificial Intelligence, and distributed machine learning (e.g., federated learning). We also identify the emerging applications of MEC in pandemic, industrial Internet of Things and disaster management. The book allows an easy cross-reference owing to the broad coverage on both the principle and applications of MEC. The book is written for people interested in communications and computer networks at all levels. The primary audience includes senior undergraduates, postgraduates, educators, scientists, researchers, developers, engineers, innovators and research strategists
Data Management in Location-Dependent Information Services: Challenges and Issues
this article, we discuss location -dependent information access in a mobile-pervasive environment, in particular in a cellular mobile system, and present new research issues arising from on-demand access, broadcast, and data cachin
Mission-Critical Communications from LMR to 5G: a Technology Assessment approach for Smart City scenarios
Radiocommunication networks are one of the main support tools of agencies that carry out
actions in Public Protection & Disaster Relief (PPDR), and it is necessary to update these
communications technologies from narrowband to broadband and integrated to information
technologies to have an effective action before society. Understanding that this problem
includes, besides the technical aspects, issues related to the social context to which these
systems are inserted, this study aims to construct scenarios, using several sources of
information, that helps the managers of the PPDR agencies in the technological decisionmaking
process of the Digital Transformation of Mission-Critical Communication considering
Smart City scenarios, guided by the methods and approaches of Technological Assessment
(TA).As redes de radiocomunicações são uma das principais ferramentas de apoio dos órgãos que
realizam ações de Proteção Pública e Socorro em desastres, sendo necessário atualizar essas
tecnologias de comunicação de banda estreita para banda larga, e integra- las às tecnologias
de informação, para se ter uma atuação efetiva perante a sociedade . Entendendo que esse
problema inclui, além dos aspectos técnicos, questões relacionadas ao contexto social ao qual
esses sistemas estão inseridos, este estudo tem por objetivo a construção de cenários,
utilizando diversas fontes de informação que auxiliem os gestores destas agências na tomada
de decisão tecnológica que envolve a transformação digital da Comunicação de Missão Crítica
considerando cenários de Cidades Inteligentes, guiado pelos métodos e abordagens de
Avaliação Tecnológica (TA)
A network paradigm for very high capacity mobile and fixed telecommunications ecosystem sustainable evolution
For very high capacity networks (VHC), the main objective is to improve the
quality of the end-user experience. This implies compliance with key
performance indicators (KPIs) required by applications. Key performance
indicators at the application level are throughput, download time, round trip
time, and video delay. They depend on the end-to-end connection between the
server and the end-user device. For VHC networks, Telco operators must provide
the required application quality. Moreover, they must meet the objectives of
economic sustainability. Today, Telco operators rarely achieve the above
objectives, mainly due to the push to increase the bit-rate of access networks
without considering the end-to-end KPIs of the applications. The main
contribution of this paper concerns the definition of a deployment framework to
address performance and cost issues for VHC networks. We show three actions on
which it is necessary to focus. First, limiting bit-rate through video
compression. Second, contain the rate of packet loss through artificial
intelligence algorithms for line stabilization. Third, reduce latency (i.e.,
round-trip time) with edge-cloud computing. The concerted and gradual
application of these measures can allow a Telco to get out of the
ultra-broadband "trap" of the access network, as defined in the paper. We
propose to work on end-to-end optimization of the bandwidth utilization ratio.
This leads to a better performance experienced by the end-user. It also allows
a Telco operator to create new business models and obtain new revenue streams
at a sustainable cost. To give a clear example, we describe how to realize
mobile virtual and augmented reality, which is one of the most challenging
future services.Comment: 42 pages, 4 tables, 6 figures. v2: Revised Englis
Reducing Cache Contention On GPUs
The usage of Graphics Processing Units (GPUs) as an application accelerator has become increasingly popular because, compared to traditional CPUs, they are more cost-effective, their highly parallel nature complements a CPU, and they are more energy efficient. With the popularity of GPUs, many GPU-based compute-intensive applications (a.k.a., GPGPUs) present significant performance improvement over traditional CPU-based implementations. Caches, which significantly improve CPU performance, are introduced to GPUs to further enhance application performance. However, the effect of caches is not significant for many cases in GPUs and even detrimental for some cases. The massive parallelism of the GPU execution model and the resulting memory accesses cause the GPU memory hierarchy to suffer from significant memory resource contention among threads. One cause of cache contention arises from column-strided memory access patterns that GPU applications commonly generate in many data-intensive applications. When such access patterns are mapped to hardware thread groups, they become memory-divergent instructions whose memory requests are not GPU hardware friendly, resulting in serialized access and performance degradation. Cache contention also arises from cache pollution caused by lines with low reuse. For the cache to be effective, a cached line must be reused before its eviction. Unfortunately, the streaming characteristic of GPGPU workloads and the massively parallel GPU execution model increase the reuse distance, or equivalently reduce reuse frequency of data. In a GPU, the pollution caused by a large reuse distance data is significant. Memory request stall is another contention factor. A stalled Load/Store (LDST) unit does not execute memory requests from any ready warps in the issue stage. This stall prevents the potential hit chances for the ready warps. This dissertation proposes three novel architectural modifications to reduce the contention: 1) contention-aware selective caching detects the memory-divergent instructions caused by the column-strided access patterns, calculates the contending cache sets and locality information and then selectively caches; 2) locality-aware selective caching dynamically calculates the reuse frequency with efficient hardware and caches based on the reuse frequency; and 3) memory request scheduling queues the memory requests from a warp issuing stage, frees the LDST unit stall and schedules items from the queue to the LDST unit by multiple probing of the cache. Through systematic experiments and comprehensive comparisons with existing state-of-the-art techniques, this dissertation demonstrates the effectiveness of our aforementioned techniques and the viability of reducing cache contention through architectural support. Finally, this dissertation suggests other promising opportunities for future research on GPU architecture
The Road Ahead for Networking: A Survey on ICN-IP Coexistence Solutions
In recent years, the current Internet has experienced an unexpected paradigm
shift in the usage model, which has pushed researchers towards the design of
the Information-Centric Networking (ICN) paradigm as a possible replacement of
the existing architecture. Even though both Academia and Industry have
investigated the feasibility and effectiveness of ICN, achieving the complete
replacement of the Internet Protocol (IP) is a challenging task.
Some research groups have already addressed the coexistence by designing
their own architectures, but none of those is the final solution to move
towards the future Internet considering the unaltered state of the networking.
To design such architecture, the research community needs now a comprehensive
overview of the existing solutions that have so far addressed the coexistence.
The purpose of this paper is to reach this goal by providing the first
comprehensive survey and classification of the coexistence architectures
according to their features (i.e., deployment approach, deployment scenarios,
addressed coexistence requirements and architecture or technology used) and
evaluation parameters (i.e., challenges emerging during the deployment and the
runtime behaviour of an architecture). We believe that this paper will finally
fill the gap required for moving towards the design of the final coexistence
architecture.Comment: 23 pages, 16 figures, 3 table
Security and Privacy for Green IoT-based Agriculture: Review, Blockchain solutions, and Challenges
open access articleThis paper presents research challenges on security and privacy issues in the field of green IoT-based agriculture. We start by describing a four-tier green IoT-based agriculture architecture and summarizing the existing surveys that deal with smart agriculture. Then, we provide a classification of threat models against green IoT-based agriculture into five categories, including, attacks against privacy, authentication, confidentiality, availability, and integrity properties. Moreover, we provide a taxonomy and a side-by-side comparison of the state-of-the-art methods toward secure and privacy-preserving technologies for IoT applications and how they will be adapted for green IoT-based agriculture. In addition, we analyze the privacy-oriented blockchain-based solutions as well as consensus algorithms for IoT applications and how they will be adapted for green IoT-based agriculture. Based on the current survey, we highlight open research challenges and discuss possible future research directions in the security and privacy of green IoT-based agriculture
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