Skip to Main Content
In the past several years, there are various technologies emerging, which are either directly or indirectly related to communication. Some of them are over the evolution of traditional communication systems, while others are over new systems such as smart grids, molecular networks, and big data systems.
In this special issue, we cover some recent results in the following four emerging areas: 5G cellular systems, big data systems, bio/nano/molecular networks, and smart grids.
Specifically, for 5G, we have included six papers.
The paper 5G-Enabled Tactile Internet presents the most important concepts, which lay at the intersection between the tactile Internet and the emerging 5G systems. The paper outlines the key technical requirements and architectural approaches for the tactile Internet, pertaining to wireless access protocols, radio resource management aspects, next generation core networking capabilities, edge-cloud, and edge-AI capabilities.
The paper New Paradigm of 5G Wireless Internet provides an overview of China Mobile’s 5G vision and potential solutions. The 5G network design considerations are discussed, including cloud radio access network (C-RAN), ultra-dense network (UDN), software defined network (SDN), and network function virtualization (NFV), examined as key potential solutions toward a green, soft, and super fast 5G network.
The paper On Service Resilience in Cloud-Native 5G Mobile Systems introduces a unified framework, along with efficient and proactive restoration mechanisms, to ensure service resilience in carrier cloud. As restoration of a network function failure impacts a potential number of users, adequate network overload control mechanisms are discussed. A mathematical model is developed to evaluate the performance of the proposed mechanisms.
The paper Low-Complexity MIMO Non-Linear Precoding Using Degree-2 Sparse Vector Perturbation investigates the fundamental problem of MU-MIMO scalability tackled through a novel signal-processing approach, which is called degree-2 vector perturbation (D2VP). Unlike the conventional VP approaches that aim at minimizing the transmit-to-receive energy ratio through searching over an N-dimensional Euclidean space, D2VP shares the same target through iterative searching over two optimally selected subspaces. By this means, the computational complexity is managed to be in the cubic order of the size of MU-MIMO networks.
The paper Internet of Things in the 5G Era: Enablers, Architecture and Business Models analyzes in detail the potential of 5G technologies for IoT, by considering both the technological and standardization aspects. The present-day IoT connectivity landscape is reviewed, as well as the main 5G enablers for the IoT. In addition, massive business shifts that a tight link between IoT and 5G may cause in the operator and vendors ecosystem are discussed.
The paper User Mobility Evaluation for 5G Small Cell Networks Based on Individual Mobility Model derives user pause, arrival, and departure probabilities for evaluating the user mobility performance in a hotspot-type 5G small cell network. Furthermore, coverage probabilities of small cell and macro cell BSs are derived for all the users in the 5G small cell networks, respectively.
For big data systems, we have three papers.
The paper Negatively Correlated Search presents a novel and efficient evolutionary algorithm, namely Negatively Correlated Search (NCS), which maintains multiple individual search processes in parallel and models the search behaviors of individual search processes as probability distributions.
The paper Analyzing Enterprise Storage Workloads with Graph Modeling and Clustering presents a novel graph analytics framework, GraphLens, for mining, and analyzing real world storage traces. The evaluation on real storage traces shows that GraphLens can provide broad and deep trace analysis for better storage strategy planning and efficient data placement guidance.
The paper Big Data for Autonomic Intercontinental Overlays shows that intercontinental Internet Protocol (IP) paths are far from optimal with respect to Quality of Service (QoS) metrics such as end-to-end round-trip delay based on the collection of data sampled over a large number of source–destinations pairs. It presents a machine learning-based scheme to exploit large scale datasets collected from communicating node pairs in a multihop overlay network that uses IP between the overlay nodes, and selects paths that provide substantially better QoS than IP.
For bio/nano/molecular networks, we have three papers.
The paper Queuing Models for Abstracting Interactions in Bacterial Communities considers communication models for populations of bacteria, particularly those that communicate via quorum sensing, or via electron exchange. It is shown that models based on queues may be used to describe and analyze this kind of communication, which is important to the study of microbiology and may have applications in medicine or nanotechnology.
The paper Molecular MIMO: From Theory to Prototype discusses the use of multiple transmitters and receivers in nanoscale biological and molecular communications systems. In conventional radio frequency wireless communications, it is well known that using multiple antennas at both ends of the radio link can significantly increase the data capacity of the system. This paper uses detailed modeling techniques to demonstrate that similar performance gains can be attained in molecular communication setups. Detection algorithms for this configuration are also proposed and analyzed. An initial laboratory experimental system is also described to show an initial verification of this principle for a communications system using multiple chemical receivers to detect multiple alcohol sprays.
The paper Analysis of Error Detection Schemes in Diffusion-based Molecular Communication considers physical layer aspects of molecular communication, particularly when ON/OFF keying is used, where molecular communication channels face important complexity constraints, as well as the challenges of the channel physics. Coding schemes (particularly error-detecting schemes) are developed, which explicitly take into account the complexity limitations of biological agents.
For smart grids, we have five papers.
The paper An Online Gradient Algorithm for Optimal Power Flow on Radial Networks proposes an online algorithm to solve the optimal power flow problems on radial networks. An important feature of the proposed gradient projection algorithm is that the intermediate iterates always satisfy power flow equations and operational constraints. It shows that the proposed algorithm converges to the set of local optima and provides sufficient conditions under which it converges to a global optimum.
The paper Joint Optimal Design and Operation of Hybrid Energy Storage Systems studies the problem of jointly optimizing the sizing and the operating strategy of a hybrid energy storage system. The solution provides a Pareto-optimal frontier of the sizes of the underlying storage technologies. The proposed framework is used to analyze two concrete case studies.
The paper Robust Workload and Energy Management for Sustainable Data Centers uses a robust optimization framework to study the problem of integrating renewable energy sources, distributed storage units, cooling facilities, and dynamic pricing into the workload and energy management tasks of a data center network. It aims to minimize the system’s worst-case net cost subject to the operational constraints of data center. Numerical results with real data corroborate the merits of the proposed framework.
The paper Renewables and Storage in Distribution Systems: Centralized vs. Decentralized Integration studies the problem of integrating renewables and storage into a distribution network. Both the centralized integration and decentralized integration models are analyzed using Stackelberg games. The tradeoff between the consumer surplus and retail profit of the utility is investigated.
The paper Assessment of LTE Wireless Access for Monitoring of Energy Distribution in the Smart Grid discusses how the fourth generation long term evolution wireless networks can support data from future smart grid devices including smart meters. In smart grid applications, a very large number of devices in one cell may periodically access the network to send data. The authors show through detailed analysis that conventional protocols that enable devices to access the Internet wirelessly may not cope very well in this scenario, due to the significant increase in the expected number of devices. It shows that a significant redesign of the long term evolution system is required to support future smart grid data traffic efficiently.
It is the editorial team’s objective that these results could motivate more research efforts in these areas.
Back to Top