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Emerging applications such as augmented reality and tactile Internet are compute-intensive and latency sensitive, which hampers their running in constrained end devices alone or in the distant cloud. The stringent requirements of such applications have given rise to the realization of edge computing, wherby computation is offloaded near to users. Compute-less networking is an extension of edge computing that aims to reduce computation and abridge communication by adopting in-network computing and computation reuse. Computation reuse aims to cache the result of computations and use them to perform similar tasks in the future and, therefore, avoid redundant calculations and optimize the use of resources. In this article, we focus on the correctness of the final output produced by computation reuse. Since the input might not be identical but similar, the reuse of previous computation raises questions about the accuracy of the final results. To this end, we implement a proof of concept to study and gauge the effectiveness and efficiency of computation reuse. We are able to reduce task completion time by up to 80 percent while ensuring high correctness. We further discuss open challenges and highlight future research directions. [ABSTRACT FROM AUTHOR]

The exponential growth of distributed energy resources is enabling the transformation of traditional consumers in the smart grid into prosumers. This transition presents a promising opportunity for sustainable energy trading. However, the integration of prosumers in the energy market imposes new considerations in designing unified and sustainable frameworks for efficient use of the power and communication infrastructure. Furthermore, several issues need to be tackled to adequately promote the adoption of decentralized renewable-energy-oriented systems, such as communication overhead, data privacy, scalability, and sustainability. In this article, we present the different aspects and challenges to be addressed for building efficient energy trading markets in relation to communication and smart decision making. Accordingly, we propose a multi-level pro-decision framework for prosumer communities to achieve collective goals. Since the individual decisions of prosumers are mainly driven by individual self-sufficiency goals, the framework prioritizes the individual prosumers' decisions and relies on the 5G wireless network for fast coordination among community members. In fact, each prosumer predicts energy production and consumption to make proactive trading decisions as a response to collective-level requests. Moreover, the collaboration of the community is further extended by including the collaborative training of prediction models using federated learning, assisted by edge servers and prosumer home area equipment. In addition to preserving prosumers' privacy, we show through evaluations that training prediction models using federated learning yields high accuracy for different energy resources while reducing the communication overhead. [ABSTRACT FROM AUTHOR]

Biomechanics is a scientific discipline that studies the forces acting on a body and the effects they produce. In this article, we bring together biomechanists and networking researchers to shed light on how research efforts in biomechanics, primarily related to the study of the human body, can be facilitated through networking and computing technologies, such as edge and cloud computing, software defined networking, and information-centric networking. We first present challenges related to networking and computing that biomechanists face today, and we then describe how networking and computing technologies can address them. Finally, we identify directions for future networking research with a focus on biomechanics to facilitate and encourage interdisciplinary collaborations between biomechanists and networking researchers. [ABSTRACT FROM AUTHOR]

Information-Centric Networking (ICN) has emerged as a paradigm to cope with the lack of built-in security primitives and efficient mechanisms for content distribution of today's Internet. However, deploying ICN in a wireless environment poses a different set of challenges compared to a wired environment, especially when it comes to security. In this article, we present the security issues that may arise and the attacks that may occur from different points of view when ICN is deployed in wireless environments. The discussed attacks may target both applications and the ICN network itself by exploiting elements of the ICN architecture, such as content names and in-network content caches. Furthermore, we discuss potential solutions to the presented issues and countermeasures to the presented attacks. Finally, we identify future research opportunities and directions. [ABSTRACT FROM AUTHOR]

Delay-sensitive applications have been driving the move away from cloud computing, which cannot meet their low-latency requirements. Edge computing and programmable switches have been among the first steps toward pushing computation closer to end-users in order to reduce cost, latency, and overall resource utilization. This article presents the "compute-less" paradigm, which builds on top of the well known edge computing paradigm through a set of communication and computation optimization mechanisms (e.g.,, in-network computing, task clustering and aggregation, computation reuse). The main objective of the compute-less paradigm is to reduce the migration of computation and the usage of network and computing resources, while maintaining high Quality of Experience for end-users. We discuss the new perspectives, challenges, limitations, and opportunities of this compute-less paradigm. [ABSTRACT FROM AUTHOR]

information-Centric Networking (iCN) is a promising candidate architecture for the future internet that leverages the content name instead of the source of the content (host address). iCN decouples the content from its original location and owner, and enables in-network caching at the network layer. Similarly, the inception of ioT has enabled futuristic applications and services in almost every walk of life. Due to the nature of internet of Things (ioT) applications, traditional TCP/iP-based internet architecture faces challenges such as addressing, heterogeneity, availability, scalability, and resource constraints. Therefore, iCN can be a suitable choice to address these challenges in ioT applications. Among other features of iCN, the in-network caching feature increases the availability and efficiency of content- sharing in ioT networks. Therefore, it is essential to have efficient cache placement strategies in iCN to increase its utility. in this regard, in this article, we propose an iCN cache placement strategy at the edge network for ioT applications. More precisely, we design a distributed cache placement scheme that aims to push the popular content to the edge network and keep the relatively less-popular content at the core. We also propose a collaborative mechanism to fetch content from the nearest neighbor's content-store as well as propose a cache replacement policy based on the content popularity. Through extensive simulations, we evaluate the proposed scheme and the obtained results show the efficiency and out-performance against similar strategies in the literature. [ABSTRACT FROM AUTHOR]

The information-centric networking model uses content as the fundamental element, which can be cached and redistributed within the network. In a large-scale, wireless Internet of Things network, this improves efficiency significantly, but also renders many host-centric security solutions obsolete. This article discusses security and privacy challenges in a merged paradigm. [ABSTRACT FROM AUTHOR]

ICN architectures use pull-based communication with single interest response pairs. Content retrieval using this model is very efficient when the content already exists in the network. Subscription services for content that is being dynamically generated or will be generated in the future, do not work well with pull based systems. In this work we investigate ICN as a publisher-subscriber communication enabler, and present its challenges and limitations. Based on the observations, we propose a group-based subscription architecture, which enables not only a seamless publisher-subscriber model, but also authentication, access control, and group management features, without modifying ICN principles. Compared to traditional pull-based subscription, we are able to achieve lower control overhead with added security and privacy features. The performance analysis also shows that with semi-persistent interest, the memory requirements of the core nodes can be kept at minimal levels. We also identify interesting research challenges which can enable a rich ICN ecosystem for different types of services. [ABSTRACT FROM AUTHOR]

Various Internet solutions take their power processing and analysis from cloud computing services. Internet of Things (IoT) applications started discovering the benefits of computing, processing, and analysis on the device itself aiming to reduce latency for time-critical applications. However, on-device processing is not suitable for resource-constraints IoT devices. Edge computing (EC) came as an alternative solution that tends to move services and computation more closer to consumers, at the edge. In this letter, we study and discuss the applicability of merging deep learning (DL) models, i.e., convolutional neural network (CNN), recurrent neural network (RNN), and reinforcement learning (RL), with IoT and information-centric networking which is a promising future Internet architecture, combined all together with the EC concept. Therefore, a CNN model can be used in the IoT area to exploit reliably data from a complex environment. Moreover, RL and RNN have been recently integrated into IoT, which can be used to take the multi-modality of data in real-time applications into account. [ABSTRACT FROM AUTHOR]

Due to the proliferation of Internet of Things (IoT) and application/user demands that challenge communication and computation, edge computing has emerged as the paradigm to bring computing resources closer to users. In this paper, we present Whispering , an analytical model for the migration of services (service offloading) from the cloud to the edge, in order to minimize the completion time of computational tasks offloaded by user devices and improve the utilization of resources. We also empirically investigate the impact of reusing the results of previously executed tasks for the execution of newly received tasks (computation reuse) and propose an adaptive task offloading scheme between edge and cloud. Our evaluation results show that Whispering achieves up to 35% and 97% (when coupled with computation reuse) lower task completion times than cases where tasks are executed exclusively at the edge or the cloud.