521 research outputs found
Real-Time IoV Task Offloading through Dynamic Assignment of SDN Controllers: Algorithmic Approaches and Performance Evaluation
Task offloading in Internet of Vehicles (IoV) is very crucial. The widespread use of IoT applications frequently interacts with the cloud, thereby increasing the load on centralized cloud controllers. Centralized network management in cloud infrastructure is not feasible for the latest IoT trends. Decentralized and decoupled network management in Software Defined Networks (SDN) can enhance IoV services. SDN and IoV coupling can better handle task offloading in ubiquitous and dynamic IoV environments. However, appropriate SDN controller assignment and allotment strategies play a prominent role in IoV communication. In this study, we developed algorithms for SDN controller assignment and allotment namely 1) Next Fit Allotment and Assignment of SDN Controller in IoV (NFAAC), 2) Dynamic Bin Packing Allotment and Assignment of SDN Controller in IoV (DBPAAC), and 3) Dynamic Focused and Bidding Allotment and Assignment algorithm of SDN Controller in IoV (DFBAAC). These algorithms were simulated using open-flow switch controllers. The controllers were modeled as Road Side Units (RSU) that can allocate bandwidth and resource requirements to vehicles on the road. Our results show that our proposed algorithm works efficiently for SDN controller assignment and allocation, outperforming the existing work by a significant improvement of 13.5%. The working of the proposed algorithms are verified, tested, and analytically presented in this study
Impatient Queuing for Intelligent Task Offloading in Multi-Access Edge Computing
Multi-access edge computing (MEC) emerges as an essential part of the
upcoming Fifth Generation (5G) and future beyond-5G mobile communication
systems. It adds computational power towards the edge of cellular networks,
much closer to energy-constrained user devices, and therewith allows the users
to offload tasks to the edge computing nodes for low-latency applications with
very-limited battery consumption. However, due to the high dynamics of user
demand and server load, task congestion may occur at the edge nodes resulting
in long queuing delay. Such delays can significantly degrade the quality of
experience (QoE) of some latency-sensitive applications, raise the risk of
service outage, and cannot be efficiently resolved by conventional queue
management solutions.
In this article, we study a latency-outage critical scenario, where users
intend to limit the risk of latency outage. We propose an impatience-based
queuing strategy for such users to intelligently choose between MEC offloading
and local computation, allowing them to rationally renege from the task queue.
The proposed approach is demonstrated by numerical simulations to be efficient
for generic service model, when a perfect queue status information is
available. For the practical case where the users obtain only imperfect queue
status information, we design an optimal online learning strategy to enable its
application in Poisson service scenarios.Comment: To appear in IEEE Transactions on Wireless Communication
Integration of Blockchain and Auction Models: A Survey, Some Applications, and Challenges
In recent years, blockchain has gained widespread attention as an emerging
technology for decentralization, transparency, and immutability in advancing
online activities over public networks. As an essential market process,
auctions have been well studied and applied in many business fields due to
their efficiency and contributions to fair trade. Complementary features
between blockchain and auction models trigger a great potential for research
and innovation. On the one hand, the decentralized nature of blockchain can
provide a trustworthy, secure, and cost-effective mechanism to manage the
auction process; on the other hand, auction models can be utilized to design
incentive and consensus protocols in blockchain architectures. These
opportunities have attracted enormous research and innovation activities in
both academia and industry; however, there is a lack of an in-depth review of
existing solutions and achievements. In this paper, we conduct a comprehensive
state-of-the-art survey of these two research topics. We review the existing
solutions for integrating blockchain and auction models, with some
application-oriented taxonomies generated. Additionally, we highlight some open
research challenges and future directions towards integrated blockchain-auction
models
Introduction to the Special Issue on Sustainable Solutions for the Intelligent Transportation Systems
The intelligent transportation systems improve the transportation system’s operational efficiency and enhance its safety and reliability by high-tech means such as information technology, control technology, and computer technology. In recent years, sustainable development has become an important topic in intelligent transportation’s development, including new infrastructure and energy distribution, new energy vehicles and new transportation systems, and the development of low-carbon and intelligent transportation equipment. New energy vehicles’ development is a significant part of green transportation, and its automation performance improvement is vital for smart transportation.
The development of intelligent transportation and green, low-carbon, and intelligent transportation equipment needs to be promoted, a significant feature of transportation development in the future. For intelligent infrastructure and energy
distribution facilities, the electricity for popular electric vehicles and renewable energy, such as nuclear power and hydrogen
power, should be considered
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