Showing papers on "Mobile telephony published in 2016"

Unmanned Aerial Vehicle With Underlaid Device-to-Device Communications: Performance and Tradeoffs

Abstract: In this paper, the deployment of an unmanned aerial vehicle (UAV) as a flying base station used to provide the fly wireless communications to a given geographical area is analyzed. In particular, the coexistence between the UAV, that is transmitting data in the downlink, and an underlaid device-to-device (D2D) communication network is considered. For this model, a tractable analytical framework for the coverage and rate analysis is derived. Two scenarios are considered: a static UAV and a mobile UAV. In the first scenario, the average coverage probability and the system sum-rate for the users in the area are derived as a function of the UAV altitude and the number of D2D users. In the second scenario, using the disk covering problem, the minimum number of stop points that the UAV needs to visit in order to completely cover the area is computed. Furthermore, considering multiple retransmissions for the UAV and D2D users, the overall outage probability of the D2D users is derived. Simulation and analytical results show that, depending on the density of D2D users, the optimal values for the UAV altitude, which lead to the maximum system sum-rate and coverage probability, exist. Moreover, our results also show that, by enabling the UAV to intelligently move over the target area, the total required transmit power of UAV while covering the entire area, can be minimized. Finally, in order to provide full coverage for the area of interest, the tradeoff between the coverage and delay, in terms of the number of stop points, is discussed.

Ultra-Dense Networks: A Survey

Abstract: The exponential growth and availability of data in all forms is the main booster to the continuing evolution in the communications industry. The popularization of traffic-intensive applications including high definition video, 3-D visualization, augmented reality, wearable devices, and cloud computing defines a new era of mobile communications. The immense amount of traffic generated by today’s customers requires a paradigm shift in all aspects of mobile networks. Ultradense network (UDN) is one of the leading ideas in this racetrack. In UDNs, the access nodes and/or the number of communication links per unit area are densified. In this paper, we provide a survey-style introduction to dense small cell networks. Moreover, we summarize and compare some of the recent achievements and research findings. We discuss the modeling techniques and the performance metrics widely used to model problems in UDN. Also, we present the enabling technologies for network densification in order to understand the state-of-the-art. We consider many research directions in this survey, namely, user association, interference management, energy efficiency, spectrum sharing, resource management, scheduling, backhauling, propagation modeling, and the economics of UDN deployment. Finally, we discuss the challenges and open problems to the researchers in the field or newcomers who aim to conduct research in this interesting and active area of research.

Optimal Workload Allocation in Fog-Cloud Computing Toward Balanced Delay and Power Consumption

Abstract: Mobile users typically have high demand on localized and location-based information services. To always retrieve the localized data from the remote cloud, however, tends to be inefficient, which motivates fog computing. The fog computing, also known as edge computing, extends cloud computing by deploying localized computing facilities at the premise of users, which prestores cloud data and distributes to mobile users with fast-rate local connections. As such, fog computing introduces an intermediate fog layer between mobile users and cloud, and complements cloud computing toward low-latency high-rate services to mobile users. In this fundamental framework, it is important to study the interplay and cooperation between the edge (fog) and the core (cloud). In this paper, the tradeoff between power consumption and transmission delay in the fog-cloud computing system is investigated. We formulate a workload allocation problem which suggests the optimal workload allocations between fog and cloud toward the minimal power consumption with the constrained service delay. The problem is then tackled using an approximate approach by decomposing the primal problem into three subproblems of corresponding subsystems, which can be, respectively, solved. Finally, based on simulations and numerical results, we show that by sacrificing modest computation resources to save communication bandwidth and reduce transmission latency, fog computing can significantly improve the performance of cloud computing.

DeepX: a software accelerator for low-power deep learning inference on mobile devices

Abstract: Breakthroughs from the field of deep learning are radically changing how sensor data are interpreted to extract the high-level information needed by mobile apps. It is critical that the gains in inference accuracy that deep models afford become embedded in future generations of mobile apps. In this work, we present the design and implementation of DeepX, a software accelerator for deep learning execution. DeepX signif- icantly lowers the device resources (viz. memory, computation, energy) required by deep learning that currently act as a severe bottleneck to mobile adoption. The foundation of DeepX is a pair of resource control algorithms, designed for the inference stage of deep learning, that: (1) decompose monolithic deep model network architectures into unit- blocks of various types, that are then more efficiently executed by heterogeneous local device processors (e.g., GPUs, CPUs); and (2), perform principled resource scaling that adjusts the architecture of deep models to shape the overhead each unit-blocks introduces. Experiments show, DeepX can allow even large-scale deep learning models to execute efficently on modern mobile processors and significantly outperform existing solutions, such as cloud-based offloading.

Incentives for Mobile Crowd Sensing: A Survey

Abstract: Recent years have witnessed the fast proliferation of mobile devices (e.g., smartphones and wearable devices) in people's lives. In addition, these devices possess powerful computation and communication capabilities and are equipped with various built-in functional sensors. The large quantity and advanced functionalities of mobile devices have created a new interface between human beings and environments. Many mobile crowd sensing applications have thus been designed which recruit normal users to contribute their resources for sensing tasks. To guarantee good performance of such applications, it's essential to recruit sufficient participants. Thus, how to effectively and efficiently motivate normal users draws growing attention in the research community. This paper surveys diverse strategies that are proposed in the literature to provide incentives for stimulating users to participate in mobile crowd sensing applications. The incentives are divided into three categories: entertainment, service, and money. Entertainment means that sensing tasks are turned into playable games to attract participants. Incentives of service exchanging are inspired by the principle of mutual benefits. Monetary incentives give participants payments for their contributions. We describe literature works of each type comprehensively and summarize them in a compact form. Further challenges and promising future directions concerning incentive mechanism design are also discussed.

Energy Efficient Mobile Cloud Computing Powered by Wireless Energy Transfer

Abstract: Achieving long battery lives or even self sustainability has been a long standing challenge for designing mobile devices. This paper presents a novel solution that seamlessly integrates two technologies, mobile cloud computing and microwave power transfer (MPT), to enable computation in passive low-complexity devices such as sensors and wearable computing devices. Specifically, considering a single-user system, a base station (BS) either transfers power to or offloads computation from a mobile to the cloud; the mobile uses harvested energy to compute given data either locally or by offloading. A framework for energy efficient computing is proposed that comprises a set of policies for controlling CPU cycles for the mode of local computing, time division between MPT and offloading for the other mode of offloading, and mode selection. Given the CPU-cycle statistics information and channel state information (CSI), the policies aim at maximizing the probability of successfully computing given data, called computing probability , under the energy harvesting and deadline constraints. The policy optimization is translated into the equivalent problems of minimizing the mobile energy consumption for local computing and maximizing the mobile energy savings for offloading which are solved using convex optimization theory. The structures of the resultant policies are characterized in closed form. Furthermore, given non-causal CSI, the said analytical framework is further developed to support computation load allocation over multiple channel realizations, which further increases the computing probability. Last, simulation demonstrates the feasibility of wirelessly powered mobile cloud computing and the gain of its optimal control.

5G Mobile and Wireless Communications Technology

Abstract: Written by leading experts in 5G research, this book is a comprehensive overview of the current state of 5G. Covering everything from the most likely use cases, spectrum aspects, and a wide range of technology options to potential 5G system architectures, it is an indispensable reference for academics and professionals involved in wireless and mobile communications. Global research efforts are summarised, and key component technologies including D2D, mm-wave communications, massive MIMO, coordinated multi-point, wireless network coding, interference management and spectrum issues are described and explained. The significance of 5G for the automotive, building, energy, and manufacturing economic sectors is addressed, as is the relationship between IoT, machine type communications, and cyber-physical systems. This essential resource equips you with a solid insight into the nature, impact and opportunities of 5G.

The iPhone Effect: The Quality of In-Person Social Interactions in the Presence of Mobile Devices

Abstract: This study examined the relationship between the presence of mobile devices and the quality of real-life in-person social interactions. In a naturalistic field experiment, 100 dyads were randomly assigned to discuss either a casual or meaningful topic together. A trained research assistant observed the participants unobtrusively from a distance during the course of a 10-min conversation noting whether either participant placed a mobile device on the table or held it in his or her hand. Using Hierarchical Linear Modeling, it was found that conversations in the absence of mobile communication technologies were rated as significantly superior compared with those in the presence of a mobile device, above and beyond the effects of age, gender, ethnicity, and mood. People who had conversations in the absence of mobile devices reported higher levels of empathetic concern. Participants conversing in the presence of a mobile device who also had a close relationship with each other reported lower levels of empathy compared with dyads who

Mobile network architecture evolution toward 5G

Abstract: As a chain is as strong as its weakest element, so are the efficiency, flexibility, and robustness of a mobile network, which relies on a range of different functional elements and mechanisms. Indeed, the mobile network architecture needs particular attention when discussing the evolution of 3GPP EPS because it is the architecture that integrates the many different future technologies into one mobile network. This article discusses 3GPP EPS mobile network evolution as a whole, analyzing specific architecture properties that are critical in future 3GPP EPS releases. In particular, this article discusses the evolution toward a "network of functions," network slicing, and software-defined mobile network control, management, and orchestration. Furthermore, the roadmap for the future evolution of 3GPP EPS and its technology components is detailed and relevant standards defining organizations are listed.

Mobile big data analytics using deep learning and apache spark

Abstract: The proliferation of mobile devices, such as smartphones and Internet of Things gadgets, has resulted in the recent mobile big data era. Collecting mobile big data is unprofitable unless suitable analytics and learning methods are utilized to extract meaningful information and hidden patterns from data. This article presents an overview and brief tutorial on deep learning in mobile big data analytics and discusses a scalable learning framework over Apache Spark. Specifically, distributed deep learning is executed as an iterative MapReduce computing on many Spark workers. Each Spark worker learns a partial deep model on a partition of the overall mobile, and a master deep model is then built by averaging the parameters of all partial models. This Spark-based framework speeds up the learning of deep models consisting of many hidden layers and millions of parameters. We use a context-aware activity recognition application with a real-world dataset containing millions of samples to validate our framework and assess its speedup effectiveness.

Efficient Algorithms for Capacitated Cloudlet Placements

Abstract: Mobile cloud computing is emerging as a main ubiquitous computing platform to provide rich cloud resources for various applications of mobile devices. Although most existing studies in mobile cloud computing focus on energy savings of mobile devices by offloading computing-intensive jobs from mobile devices to remote clouds, the access delays between mobile users and remote clouds usually are long and sometimes unbearable. Cloudlet as a new technology is capable to bridge this gap, and can enhance the performance of mobile devices significantly while meeting the crisp response time requirements of mobile users. In this paper, we study the cloudlet placement problem in a large-scale Wireless Metropolitan Area Network (WMAN) consisting of many wireless Access Points (APs). We first formulate the problem as a novel capacitated cloudlet placement problem that places $K$ cloudlets to some strategic locations in the WMAN with the objective to minimize the average access delay between mobile users and the cloudlets serving the users. We then propose an exact solution to the problem by formulating it as an Integer Linear Programming (ILP). Due to the poor scalability of the ILP, we instead propose an efficient heuristic for the problem. For a special case of the problem where all cloudlets have identical computing capacities, we devise novel approximation algorithms with guaranteed approximation ratios. We also devise an online algorithm for dynamically allocating user requests to different cloudlets, if the $K$ cloudlets have already been placed. We finally evaluate the performance of the proposed algorithms through experimental simulations. Simulation results demonstrate that the proposed algorithms are promising and scalable.

Network slicing as a service: enabling enterprises' own software-defined cellular networks

Abstract: With the blossoming of network functions virtualization and software-defined networks, networks are becoming more and more agile with features like resilience, programmability, and open interfaces, which help operators to launch a network or service with more flexibility and shorter time to market. Recently, the concept of network slicing has been proposed to facilitate the building of a dedicated and customized logical network with virtualized resources. In this article, we introduce the concept of hierarchical NSaaS, helping operators to offer customized end-to-end cellular networks as a service. Moreover, the service orchestration and service level agreement mapping for quality assurance are introduced to illustrate the architecture of service management across different levels of service models. Finally, we illustrate the process of network slicing as a service within operators by typical examples. With network slicing as a service, we believe that the supporting system will transform itself to a production system by merging the operation and business domains, and enabling operators to build network slices for vertical industries more agilely.

Licensed Spectrum Sharing Schemes for Mobile Operators: A Survey and Outlook

Abstract: The ongoing development of mobile communication networks to support a wide range of superfast broadband services has led to massive capacity demand. This problem is expected to be a significant concern during the deployment of the 5G wireless networks. The demand for additional spectrum to accommodate mobile services supporting higher data rates and having lower latency requirements, as well as the need to provide ubiquitous connectivity with the advent of the Internet of Things sector, is likely to considerably exceed the supply, based on the current policy of exclusive spectrum allocation to mobile cellular systems. Hence, the imminent spectrum shortage has introduced a new impetus to identify practical solutions to make the most efficient use of scarce licensed bands in a shared manner. Recently, the concept of dynamic spectrum sharing has received considerable attention from regulatory bodies and governments globally, as it could potentially open new opportunities for mobile operators to exploit spectrum bands whenever they are underutilized by their owners, subject to service level agreements. Although various sharing paradigms have been proposed and discussed, the impact and performance gains of different schemes can be scenario-specific, and may vary depending on the nature of the sharing players, the level of sharing and spectrum access scheme. In this survey, we study the main concepts of dynamic spectrum sharing, different sharing scenarios, as well as the major challenges associated with sharing of licensed bands. Finally, we conclude this survey with open research challenges and suggest some future research directions.

Practical attacks against privacy and availability in 4G/LTE mobile communication systems

Abstract: Mobile communication systems now constitute an essential part of life throughout the world. Fourth generation "Long Term Evolution" (LTE) mobile communication networks are being deployed. The LTE suite of specifications is considered to be significantly better than its predecessors not only in terms of functionality but also with respect to security and privacy for subscribers. We carefully analyzed LTE access network protocol specifications and uncovered several vulnerabilities. Using commercial LTE mobile devices in real LTE networks, we demonstrate inexpensive, and practical attacks exploiting these vulnerabilities. Our first class of attacks consists of three different ways of making an LTE device leak its location: A semi-passive attacker can locate an LTE device within a 2 sq.km area within a city whereas an active attacker can precisely locate an LTE device using GPS co-ordinates or trilateration via cell-tower signal strength information. Our second class of attacks can persistently deny some or all services to a target LTE device. To the best of our knowledge, our work constitutes the first publicly reported practical attacks against LTE access network protocols. We present several countermeasures to resist our specific attacks. We also discuss possible trade-offs that may explain why these vulnerabilities exist and recommend that safety margins introduced into future specifications to address such trade-offs should incorporate greater agility to accommodate subsequent changes in the trade-off equilibrium.

Mobility-aware caching for content-centric wireless networks: modeling and methodology

Abstract: As mobile services are shifting from connection- centric communications to content-centric communications, content-centric wireless networking emerges as a promising paradigm to evolve the current network architecture Caching popular content at the wireless edge, including base stations and user terminals, provides an effective approach to alleviate the heavy burden on backhaul links, as well as lower delays and deployment costs In contrast to wired networks, a unique characteristic of content-centric wireless networks (CCWNs) is the mobility of mobile users While it has rarely been considered by existing works on caching design, user mobility contains various helpful side information that can be exploited to improve caching efficiency at both BSs and user terminals In this article, we present a general framework for mobility-aware caching in CCWNs Key properties of user mobility patterns that are useful for content caching are first identified, and then different design methodologies for mobility-aware caching are proposed Moreover, two design examples are provided to illustrate the proposed framework in detail, and interesting future research directions are identified

Cost Aware Service Placement and Load Dispatching in Mobile Cloud Systems

Abstract: With proliferation of smart phones and an increasing number of services provisioned by clouds, it is commonplace for users to request cloud services from their mobile devices. Accessing services directly from the Internet data centers inherently incurs high latency due to long RTTs and possible congestions in WAN. To lower the latency, some researchers propose to ‘cache’ the services at edge clouds or smart routers in the access network which are closer to end users than the Internet cloud. Although ‘caching’ is a promising technique, placing the services and dispatching users’ requests in a way that can minimize the users’ access delay and service providers’ cost has not been addressed so far. In this paper, we study the joint optimization of service placement and load dispatching in the mobile cloud systems. We show this problem is unique to both the traditional caching problem in mobile networks and the content distribution problem in content distribution networks. We develop a set of efficient algorithms for service providers to achieve various trade-offs among the average latency of mobile users’ requests, and the cost of service providers. Our solution utilizes user's mobility pattern and services access pattern to predict the distribution of user's future requests, and then adapt the service placement and load dispatching online based on the prediction. We conduct extensive trace driven simulations. Results show our solution not only achieves much lower latency than directly accessing service from remote clouds, but also outperforms other classical benchmark algorithms in term of the latency, cost and algorithm running time.

Big Data Driven Mobile Traffic Understanding and Forecasting: A Time Series Approach

Abstract: Understanding and forecasting mobile traffic of large scale cellular networks is extremely valuable for service providers to control and manage the explosive mobile data, such as network planning, load balancing, and data pricing mechanisms. This paper targets at extracting and modeling traffic patterns of 9,000 cellular towers deployed in a metropolitan city. To achieve this goal, we design, implement, and evaluate a time series analysis approach that is able to decompose large scale mobile traffic into regularity and randomness components. Then, we use time series prediction to forecast the traffic patterns based on the regularity components. Our study verifies the effectiveness of our utilized time series decomposition method, and shows the geographical distribution of the regularity and randomness component. Moreover, we reveal that high predictability of the regularity component can be achieved, and demonstrate that the prediction of randomness component of mobile traffic data is impossible.

Mobile Phone Computing and the Internet of Things: A Survey

Abstract: As the Internet of Things (IoT) and the Web of Things (WoT) are becoming a reality, their interconnection with mobile phone computing is increasing. Mobile phone integrated sensors offer advanced services, which when combined with Web-enabled real-world devices located near the mobile user (e.g., body area networks, radio-frequency identification tags, energy monitors, environmental sensors, etc.), have the potential of enhancing the overall user knowledge, perception and experience, encouraging more informed choices and better decisions. This paper serves as a survey of the most significant work performed in the area of mobile phone computing combined with the IoT/WoT. A selection of over 100 papers is presented, which constitute the most significant work in the field up to date, categorizing these papers into ten different domains, according to the area of application (i.e., health, sports, gaming, transportation, and agriculture), the nature of interaction (i.e., participatory sensing, eco-feedback, actuation, and control), or the communicating actors involved (i.e., things and people). Open issues and research challenges are identified, analyzed and discussed.

Why to decouple the uplink and downlink in cellular networks and how to do it

Abstract: Ever since the inception of mobile telephony, the downlink and uplink of cellular networks have been coupled, that is, mobile terminals have been constrained to associate with the same base station in both the downlink and uplink directions. New trends in network densification and mobile data usage increase the drawbacks of this constraint, and suggest that it should be revisited. In this article we identify and explain five key arguments in favor of downlink/uplink decoupling based on a blend of theoretical, experimental, and architectural insights. We then overview the changes needed in current LTE-A mobile systems to enable this decoupling, and then look ahead to fifth generation cellular standards. We demonstrate that decoupling can lead to significant gains in network throughput, outage, and power consumption at a much lower cost compared to other solutions that provide comparable or lower gains.

ECG Authentication for Mobile Devices

Abstract: Traditional mobile login methods, like numerical or graphical passwords, are vulnerable to passive attacks. It is common for intruders to gain access to personal information of their victims by watching them enter their passwords into their mobile screens from a close proximity. With this in mind, a mobile biometric authentication algorithm based on electrocardiogram (ECG) is proposed. With this algorithm, the user will only need to touch two ECG electrodes (lead I) of the mobile device to gain access. The algorithm was tested with a cell phone case heart monitor in a controlled laboratory experiment at different times and conditions with ten subjects and also with 73 records obtained from the Physionet database. The obtained results reveal that our algorithm has 1.41% false acceptance rate and 81.82% true acceptance rate with 4 s of signal acquisition. To the best of our knowledge, this is the first approach on mobile authentication that uses ECG biometric signals and it shows a promising future for this technology. Nonetheless, further improvements are still needed to optimize accuracy while maintaining a short acquisition time for authentication.

An overview of the CPRI specification and its application to C-RAN-based LTE scenarios

Abstract: The CPRI specification has been introduced to enable the communication between radio equipment and radio equipment controllers, and is of particular interest for mobile operators willing to deploy their networks following the novel cloud radio access network approach. In such a case, CPRI provides an interface for the interconnection of remote radio heads with a baseband unit by means of the so-called fronthaul network. This article presents the CPRI specification, its concept, design, and interfaces, provides a use case for fronthaul dimensioning in a realistic LTE scenario, and proposes some interesting open research challenges in the next-generation 5G mobile network.

Joint offloading decision and resource allocation for multi-user multi-task mobile cloud

Abstract: We consider a general multi-user mobile cloud computing system where each mobile user has multiple independent tasks. These mobile users share the communication resource while offloading tasks to the cloud. We aim to jointly optimize the offloading decisions of all users as well as the allocation of communication resource, to minimize the overall cost of energy, computation, and delay for all users. The optimization problem is formulated as a non-convex quadratically constrained quadratic program, which is NP-hard in general. An efficient approximate solution is proposed by using separable semidefinite relaxation, followed by recovery of the binary offloading decision and optimal allocation of the communication resource. For performance benchmark, we further propose a numerical lower bound of the minimum system cost. By comparison with this lower bound, our simulation results show that the proposed algorithm gives nearly optimal performance under various parameter settings.

Enabling Massive IoT in 5G and Beyond Systems: PHY Radio Frame Design Considerations

Abstract: The parameters of physical layer radio frame for 5th generation (5G) mobile cellular systems are expected to be flexibly configured to cope with diverse requirements of different scenarios and services. This paper presents a frame structure and design, which is specifically targeting Internet of Things (IoT) provision in 5G wireless communication systems. We design a suitable radio numerology to support the typical characteristics, that is, massive connection density and small and bursty packet transmissions with the constraint of low-cost and low complexity operation of IoT devices. We also elaborate on the design of parameters for random access channel enabling massive connection requests by IoT devices to support the required connection density. The proposed design is validated by link level simulation results to show that the proposed numerology can cope with transceiver imperfections and channel impairments. Furthermore, the results are also presented to show the impact of different values of guard band on system performance using different subcarrier spacing sizes for data and random access channels, which show the effectiveness of the selected waveform and guard bandwidth. Finally, we present system-level simulation results that validate the proposed design under realistic cell deployments and inter-cell interference conditions.

Context-Awareness for Mobile Sensing: A Survey and Future Directions

Abstract: The evolution of smartphones together with increasing computational power has empowered developers to create innovative context-aware applications for recognizing user-related social and cognitive activities in any situation and at any location. The existence and awareness of the context provide the capability of being conscious of physical environments or situations around mobile device users. This allows network services to respond proactively and intelligently based on such awareness. The key idea behind context-aware applications is to encourage users to collect, analyze, and share local sensory knowledge in the purpose for a large-scale community use by creating a smart network. The desired network is capable of making autonomous logical decisions to actuate environmental objects and also assist individuals. However, many open challenges remain, which are mostly arisen because the middleware services provided in mobile devices have limited resources in terms of power, memory, and bandwidth. Thus, it becomes critically important to study how the drawbacks can be elaborated and resolved and, at the same time, better understand the opportunities for the research community to contribute to the context-awareness. To this end, this paper surveys the literature over the period of 1991–2014 from the emerging concepts to applications of context-awareness in mobile platforms by providing up-to-date research and future research directions. Moreover, it points out the challenges faced in this regard and enlightens them by proposing possible solutions.

5G: Vision and Requirements for Mobile Communication System towards Year 2020

Abstract: The forecast for future 10 years’ traffic demand shows an increase in 1000 scales and more than 100 billion connections of Internet of Things, which imposes a big challenge for future mobile communication technology beyond year 2020. The mobile industry is struggling in the challenges of high capacity demand but low cost for future mobile network when it starts to enable a connected mobile world. 5G is targeted to shed light on these contradictory demands towards year 2020. This paper firstly forecasts the vision of mobile communication’s application in the daily life of the society and then figures out the traffic trends and demands for next 10 years from the Mobile Broadband (MBB) service and Internet of Things (IoT) perspective, respectively. The requirements from the specific service and user demands are analyzed, and the specific requirements from typical usage scenarios are calculated by the defined performance indicators. To achieve the target of affordable 5G service, the requirements from network deployment and operation perspective are also captured. Finally, the capabilities and the efficiency requirements of the 5G system are demonstrated as a flower. To realize the vision of 5G, “information a finger away, everything in touch,” 5G will provide the fiber-like access data rate, “zero” latency user experience, and connecting to more than 100 billion devices and deliver a consistent experience across a variety of scenarios with the improved energy and cost efficiency by over a hundred of times.

Optimal Energy Management Policy of Mobile Energy Gateway

Abstract: With the advancement of wireless energy harvesting and transfer technologies, eg, radio frequency (RF) energy, mobile nodes are fully untethered as energy supply is more ubiquitous The mobile nodes can receive energy from wireless chargers, which can be static or mobile In this paper, we introduce the use of a mobile energy gateway that can receive energy from a fixed charging facility, as well as move and transfer energy to other users The mobile energy gateway aims to maximize the utility by optimally taking energy charging/transferring actions We formulate the optimal energy charging/transferring problem as a Markov decision process (MDP) The MDP model is then solved to obtain the optimal energy management policy for the mobile energy gateway Furthermore, the optimal energy management policy obtained from the MDP model is proven to have a threshold structure We conduct an extensive performance evaluation of the MDP-based energy management scheme The proposed MDP-based scheme outperforms several conventional baseline schemes in terms of expected overall utility

Vehicular delay-tolerant networks for smart grid data management using mobile edge computing

Abstract: With the widespread popularity and usage of ICT around the world, there is increasing interest in replacing the traditional electric grid by the smart grid in the near future. Many smart devices exist in the smart grid environment. These devices may share their data with one another using the ICT-based infrastructure. The analysis of the data generated from various smart devices in the smart grid environment is one of the most challenging tasks to be performed as it varies with respect to parameters such as size, volume, velocity, and variety. The output of the data analysis needs to be transferred to the end users using various networks and smart appliances. But sometimes networks may become overloaded during such data transmissions to various smart devices. Consequently, significant delays may be incurred, which affect the overall performance of any implemented solution in this environment. We investigate the use of VDTNs as one of the solutions for data dissemination to various devices in the smart grid environment using mobile edge computing. VDTNs use the store-and-carry forward mechanism for message dissemination to various smart devices so that delays can be reduced during overloading and congestion situations in the core networks. As vehicles have high mobility, we propose mobile edge network support assisted by the cloud environment to manage the handoff and the processing of large data sets generated by various smart devices in the smart grid environment. In the proposed architecture, most of the computation for making decisions about charging and discharging is done by mobile devices such as vehicles located at the edge of the network (also called mobile edge computing). The computing and communication aspects are explored to analyze the impact of mobile edge computing on performance metrics such as message transmission delay, response time, and throughput to the end users using vehicles as the mobile nodes. Our empirical results demonstrate an improved performance 10-15 percent increase in throughput, 20 percent decrease in response time, and 10 percent decrease in the delay incurred with our proposed solution compared to existing state-ofthe- art solutions in the literature.

Big Data Analytics in Mobile Cellular Networks

Abstract: Mobile cellular networks have become both the generators and carriers of massive data. Big data analytics can improve the performance of mobile cellular networks and maximize the revenue of operators. In this paper, we introduce a unified data model based on the random matrix theory and machine learning. Then, we present an architectural framework for applying the big data analytics in the mobile cellular networks. Moreover, we describe several illustrative examples, including big signaling data, big traffic data, big location data, big radio waveforms data, and big heterogeneous data, in mobile cellular networks. Finally, we discuss a number of open research challenges of the big data analytics in the mobile cellular networks.