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The introduction of fifth-generation (5G) mobile networks leads to an increase in energy consumption and higher operational costs for mobile network operators (MNOs). Consequently, the optimization of 5G networks' energy efficiency is crucial, both in terms of reducing MNO costs and in terms of the negative environmental impact. However, many aspects of the 5G mobile network technology itself have been standardized, including the 5G network slicing concept. This enables the creation of multiple independent logical 5G networks within the same physical infrastructure. Since the only necessary resources in 5G networks need to be used for the realization of a specific 5G network slice, the question of whether the implementation of 5G network slicing can contribute to the improvement of 5G and future sixth-generation networks' energy efficiency arises. To tackle this question, this review paper analyzes 5G network slicing and the energy demand of different network slicing use cases and mobile virtual network operator realizations based on network slicing. The paper also overviews standardized key performance indicators for the assessment of 5G network slices' energy efficiency and discusses energy efficiency in 5G network slicing lifecycle management. In particular, to show how efficient network slicing can optimize the energy consumption of 5G networks, versatile 5G network slicing use case scenarios, approaches, and resource allocation concepts in the space, time, and frequency domains have been discussed, including artificial intelligence-based implementations of network slicing. The results of the comprehensive discussion indicate that the different implementations and approaches to network slicing pave the way for possible further reductions in 5G MNO energy costs and carbon dioxide emissions in the future. [ABSTRACT FROM AUTHOR]

Batteries are classically used as backup in case of power outages in telecommunications networks to keep the services always active. Recently, network operators use the batteries as a demand response lever, so as to reduce the energy costs and to generate revenues in the energy market. In this work, we study how the telecommunications operator can optimize the use of a battery over a given horizon to reduce energy costs and to perform load curtailments efficiently, as long as the safety usage rules are respected. First, we formulate the related optimization problem as a mixed integer program taking into account the telecommunication engineering and battery operation constraints, as well as the market rules. Second, we give two practical variants of the problem that can be solved to optimality in polynomial time thanks to a graph-oriented algorithm we propose. We also use this algorithm as a heuristic to solve efficiently the main problem. Finally, simulations based on real data from the French telecommunications operator Orange show the relevance of the model and of the graph-oriented algorithm: these prove to be computationally efficient in solving large scale instances, and significant savings and revenues can be generated through our optimized battery management policies. [ABSTRACT FROM AUTHOR]

Network slicing (NS) has emerged as a promising solution that enables network operators to slice network resources such as spectrum and bandwidth to adapt to different beyond 5G scenarios. This allows new operators to enter the market: the infrastructure provider (InP), who owns the infrastructure, and the mobile virtual network operator (MVNO), who may purchase a resource slice from the InP to provide a specific service to their end-users. To better deal with the resource allocation problem, efficient algorithms and methods have been done such as the auction model, bidding method, and game theory. This paper presents an upper-tier resource allocation based on game theory. This mechanism considers a single base station (BS) and multi MVNOs-users that share aggregated bandwidth radio access networks to maximize utilized BS resources. The proposed method takes both the bandwidth utilization of BS and the service requirements of MVNO users. Accordingly, the Game Theory solution takes two contradictory objectives: the InP aims to maximize its revenue while the MVNOs want to serve their users by paying the minimum amount. We prove that our proposal achieves an optimal solution from both InP and MVNOs' in terms of revenue and quality of service. [ABSTRACT FROM AUTHOR]

Wireless cellular networks have become increasingly important in providing data access to cellular users via a grid of cells. Many applications are considered to read data from smart meters for potable water, gas, or electricity. This paper proposes a novel algorithm to assign paired channels for intelligent metering through wireless connectivity, which is particularly relevant due to the commercial advantages that a virtual operator currently provides. The algorithm considers the behavior of secondary spectrum channels assigned to smart metering in a cellular network. It explores spectrum reuse in a virtual mobile operator to optimize dynamic channel assignment. The proposed algorithm exploits the white holes in the cognitive radio spectrum and considers the coexistence of different uplink channels, resulting in improved efficiency and reliability for smart metering. The work also defines the average user transmission throughput and total smart meter cell throughput as metrics to measure performance, providing insights into the effects of the chosen values on the overall performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Network slicing is considered to be a key feature of the 5th generation mobile networks. It permits multiple tenants, i.e. mobile virtual network operators, to share virtual resources. However, each tenant only considers the individual slice utility, which leads to unfair resource allocation among tenants. To achieve the aim that the infrastructure provider can fairly allocate virtual resources to tenants, a two‐layer resource allocation architecture in a heterogeneous radio access network (RAN) is proposed and it is formulated as a mathematical program with equilibrium constraints (MPEC). The existence of the solution in the lower layer is proved via the properties of the quasi‐variational problem, indicating that the MPEC is solvable. Combining the two‐layer architecture and successive convex approximation method, a fair algorithm is proposed, which provides fair resource allocation strategies for the infrastructure provider. Compared with the existing static slicing and social optimal methods, the analysis and simulation results confirm that the proposed algorithm weighs the utilities of the total network system and each tenant. In addition, regarding their utilities, the gap between the proposed method and the social optimal is within 5%, which outperforms static slicing. [ABSTRACT FROM AUTHOR]

Network slicing (NS) is an emerging technology in recent years, which enables network operators to slice network resources (e.g., bandwidth, power, spectrum, etc.) in different types of slices, so that it can adapt to different application scenarios of 5 g network: enhanced mobile broadband (eMBB), massive machine-type communications (mMTC) and ultra-reliable and low-latency communications (URLLC). In order to allocate these sliced network resources more effectively to users with different needs, it is important that manage the allocation of network resources. Actually, in the practical network resource allocation problem, the resources of the base station (BS) are limited and the demand of each user for mobile services is different. To better deal with the resource allocation problem, more effective methods and algorithms have emerged in recent years, such as the bidding method, deep learning (DL) algorithm, ant colony algorithm (AG), and wolf colony algorithm (WPA). This paper proposes a two tier slicing resource allocation algorithm based on Deep Reinforcement Learning (DRL) and joint bidding in wireless access networks. The wireless virtual technology divides mobile operators into infrastructure providers (InPs) and mobile virtual network operators (MVNOs). This paper considers a single base station, multi-user shared aggregated bandwidth radio access network scenario and joins the MVNOs to fully utilize base station resources, and divides the resource allocation process into two tiers. The algorithm proposed in this paper takes into account both the utilization of base station (BS) resources and the service demand of mobile users (MUs). In the upper tier, each MVNO is treated as an agent and uses a combination of bidding and Deep Q network (DQN) allows the MVNO to get more resources from the base station. In the lower tier allocation process, each MVNO distributes the received resources to the users who are connected to it, which also uses the Dueling DQN method for iterative learning to find the optimal solution to the problem. The results show that in the upper tier, the total system utility function and revenue obtained by the proposed algorithm are about 5.4% higher than double DQN and about 2.6% higher than Dueling DQN; In the lower tier, the user service quality obtained by using the proposed algorithm is more stable, the system utility function and Se are about 0.5–2.7% higher than DQN and Double DQN, but the convergence is faster. [ABSTRACT FROM AUTHOR]

In this paper, we analyze the tradeoff between the profits gained by mobile virtual network operators (MVNOs) in an orthogonal frequency division multiple access (OFDMA)-based virtualized wireless network (VWN). In this respect, MVNOs rent the network resources from a mobile network operator (MNO) to create virtual resources based on allocated rates and the cost due to allocated transmit powers in two different strategies: resource-based isolation strategy and rate-based isolation strategy. In resource-based isolation strategy, it is assumed that the whole bandwidth in each base station is divided equally between MVNOs whereas in rate-based isolation strategy, the whole bandwidth in each base station is allocated dynamically between MVNOs. We then formulate a multi-objective optimization problem (MOOP) to show the tradeoff between the maximum profit of each MVNO. To solve the formulated MOOP, we adopt the weighted Tchebycheff approach, which can provide the complete Pareto optimal region for nonconvex problems. Thus, by developing such formulation, we will be able to find the best profit gained by MVNOs. We also employ monotonic optimization to obtain the global optimal solutions of the non-convex problems by applying polyblock outer approximation algorithm. Our numerical results show the importance of the aforementioned tradeoffs and confirm that the proposed geometric programming (GP) based algorithm achieves excellent performance as compared to the monotonic method. [ABSTRACT FROM AUTHOR]

Mobile virtual network operators (MVNOs) offer mobile telecommunications services by purchasing capacity from mobile network operators (MNOs) and competing on the retail market. This study examines national data to identify possible impacts of MVNOs on the mobile market and on mobile service users. While open wholesale markets for MVNOs are relatively widespread in European countries, evidence of their impact on end users is limited due to a lack of previous research. This study uses data from the market entry of MVNOs in the Czech Republic in 2013 to estimate the impact on end users. Based on synthetic control methods, the results clearly show that the market entry of MVNOs led to a decrease in the price of calls and to a decrease in the average monthly revenue per user (ARPU) of operators. However, no significant effect on the price of data or on consumption was found. These results have some implications for policy and for the mobile industry. • A unique analysis of the impact of MVNOs market entry on prices, consumption and ARPU. • Increased market competition due to the entry of MVNOs has resulted in lower voice unit prices and total ARPU, but has no effect on data market services. • The impact of MVNOs in the dominant data market seems to be limited. [ABSTRACT FROM AUTHOR]

Wireless network virtualization is a promising solution to improve spectrum efficiency. For a wireless downlink communication system with multiple mobile virtual network operators (MVNOs), we propose a decentralized blockchain-based dynamic spectrum acquisition scheme. Our proposed scheme aims to minimize the sum transmit power at all MVNOs while satisfying the average data transmission rate thresholds. For each MVNO, the required wireless spectrum to provide customized services to the mobile users (MUs) is predicted using the half-range Gauss-Hermite quadrature. Based on the predicted values, all the MVNOs carry out a blockchain-based distributed alternative direction method of multipliers to obtain the global optimal solution to the aforementioned sum transmit power minimization problem. To examine the effectiveness of our proposed scheme, with known system parameters, we also theoretically derive the semi-closed-form solution to the actually required sum transmit power minimization problem subject to data transmission rate constraints. Simulation results illustrate that our proposed dynamic spectrum acquisition scheme achieves almost the same minimum sum power as the non-causal scheme, which assumes the number of active MUs in all cells and all the channels are known non-causally for the optimal dynamic spectrum allocation. [ABSTRACT FROM AUTHOR]

This study presents an empirical model of service quality and appropriate relationality for cellular operators, so that service users can achieve high satisfaction and loyalty. This occurs at the level of the prices offered for the lower middle segment, as well as at the level of quality for the upper middle segment. The method used is the descriptive and verification survey. The sample consists of 285 students in the third semester of eight tertiary institutions. To measure all the constructions and indicators a research questionnaire was used and the method of data analysis was SEM (Structural equation modeling). [ABSTRACT FROM AUTHOR]

Note that the delay of transmission in wireless sensor networks should be constrained within a certain range in most real-time applications. The sensors deliver data to a sink via long distance will exhausts their energy. Thus, a mobile sink, which walks back and forth within the interested region to gather the data collected by the sensors, is regarded as an effective method to ensure data gathering from monitoring sensor nodes to the mobile sink within a short communication range. In this paper, a novel virtual force-based data aggregation mechanism with mobile sink in wireless sensor networks is proposed. Firstly, a hierarchical hybrid of genetic algorithm and particle swarm optimization for distributed clustering is introduced and the whole area is divided into several grids. Secondly, the virtual force theory is adopted to calculate the virtual repulsive force of boundary, obstacles and empty area, and the virtual attractive force of the sensor nodes without being traversed. By combining all virtual forces in according with direction vectors, the residence time for mobile sink and the coordinate of the next rendezvous point can be calculated based on the force size, direction and the number of adjacent clusters. The optimal moving trajectory of sink node is then obtained to achieve high efficiency and energy saving. Consequently, the data aggregation tree can be dynamically constructed for data gathering. Finally, mobile sink node moves along the rendezvous points to aggregate the data from sensor nodes within the communication range according to the selected moving path. Simulation results show that the proposed mechanism can obtain better performance than existing algorithms in aspects of efficient data aggregation, energy saving and the path length of mobile sink. [ABSTRACT FROM AUTHOR]

In network virtualization, mobile virtual network operators (MVNOs) lease spectrum resources from mobile network operators (MNOs) and offer certain wireless services to end users. Each MVNO competes with others using optimal price and spectrum inventory so as to profit. However, the inventory of one MVNO is private information and maybe unknown to others, which makes pricing decisions difficult for MVNOs. In this work, we first study the pricing strategy given others’ inventory information. We model the pricing decision problem using the non-cooperative game theory, and develop an optimal price setting algorithm based on an ordinal potential game. Then we put forward three cooperation strategies for MVNOs and analyze the impacts of the coalitions structure on pricing decision. For the situation where the inventory of one MVNO is unknown to others, we use the Bayesian coalition formation game to formulate the pricing decision problem and propose an optimal price setting algorithm based on the Minimum Mean-Square Error to resolve the conflicts resulting from the uncertainty. Next we define a Belief Pareto Order to characterize the preferences of MVNOs regarding the coalition structures. Then we devise a distributed coalition formation algorithm with the proposed belief Pareto order to achieve a Bayesian-Nash stable coalition structure that enables each MVNO to maximize its own revenue. Finally, simulation results demonstrate comprehensive performance evaluation of the proposed game model and provide a guidance on pricing strategies for MVNOs. [ABSTRACT FROM AUTHOR]

With centralized processing, cooperative radio, and cloud infrastructure, cloud radio access network (CRAN) has attracted much attention due to its flexibility in network operation and resource management. In this paper, we propose a pricing-based resource allocation strategy in virtualized CRANs, where one mobile network operator (MNO) owns the physical resource and multiple mobile virtual network operators (MVNOs) serve their users with resources leased from the MNO. The problem is naturally formulated as a bi-level optimization problem, where the upper level corresponds to revenue maximization of the MNO and the lower level corresponds to the utility-surplus maximization of the MVNOs. To solve the problem efficiently, we propose to solve the MVNO problem with a low-complexity algorithm, which scales well with the network size. Based on the analysis of the revenue of the MNO, we find that different utility function families result in distinct revenue trends with respect to the price, and correspondingly propose efficient algorithms to find the optimal price that maximizes the revenue. Through simulations, we demonstrate that the proposed algorithm for the MVNO problem can reduce the complexity from $\mathcal {O}(M^3)$ of interior point methods to $\mathcal {O}(M)$ , where $M$ is the number of users. Meanwhile, the simulation results show that the proposed pricing methods can find the optimal price in a few iterations. [ABSTRACT FROM AUTHOR]

Abstract Telecommunication is described by enormous settled, sunk, and irreversible speculation, which makes it high-hazard undertaking. The circumstance is additionally aggravated in the mobile part by progressive ages of innovation. The introduction of Mobile Virtual Network Operators (MVNOs) added value for both operators and customers; for the operators by using their available excess capacity and for the customers by offering innovative and several niche value-added services that were not offered by Mobile Network Operators (MNOs). However, mobile operators in developing nations are urban and semi-urban based, and very few operators provide services in rural areas. There are many un-served and under-served market segments still available. The major issue for developing nations is the formulation and implementation of policies, rules, and regulations. With an extensive variety of brands, companies are willing to enter the mobile business. An exclusively exploited radio access network by mobile network operators, new concepts and strategies are required to bring the opportunity for both telecom and non-telecom organizations to take part in the mobile sector. In this paper, we aim to develop a regulatory framework for MVNO in developing nations' telecommunication market as follows: first, to carry out a thorough analysis of market and draft a feasibility study for MVNOs in the telecommunications ("telecom") market in developing nations; and second, to develop required regulations for enhanced growth opportunities in the telecom market. This can be regarded as the effort for creating infrastructure for deploying e-Government in the developing countries. Highlights • We examined deployment of Mobile Virtual Network Operator in developing nations. • A new regulatory framework and guidelines for MVNO were proposed. • We analyzed the best global practices on MVNO. • MVNO was discussed in Telecom Market where international practices are zero level. • It is a reference document for the government to put the sector into priority. [ABSTRACT FROM AUTHOR]

This article investigates the slicing concept in the 5G RAN with the related challenges and research problems. The objective is to identify the plausible options for implementing the slicing concept at the RAN level by the mobile network operator to respond to the needs of verticals. We start by identifying the different slice granularity options, that is, how to define slices by combining customer and service needs. We then present how the 5G NR features can be used for facilitating slice implementation and provide typical configurations for different slice types from technology and RAN architecture perspectives. The main challenges for RAN slicing are then discussed, with special attention to the resource allocation problem between slices sharing the same spectrum band. We also investigate the multi-tenant slicing implementation in terms of the openness of the network to third parties, which is regarded as a key issue that may encourage vertical players to use operators' networks rather than deploying their own infrastructure. [ABSTRACT FROM AUTHOR]

One of the goals of third generation partnership project (3GPP) is to deploy device to device (D2D) proximity services in both commercial and public safety settings. Furthermore, as the mobile market is nearing saturation, service providers (SPs) are searching for additional sources of revenue. Commercial D2D can make use of a SP's unused/underutilized spectrum, yet there are few feasible economic models for deploying commercial D2D services. In this paper, we present Localized Advertisements over D2D specTrum Reuse coAlition fraMework, which is a feasible economic model for deploying a localized advertisement coalition-based D2D service that exploits spectrum leasing and reuse. D2D Ad stations, i.e., user equipments, interested in providing the D2D service form a coalition in order to share spectrum allocated by the SP. Using game theory we design an incentive compatible resource determination mechanism and auction. In the auction localized advertisers compete for resources. We show that our auction approximates the profit performance characteristics of the vickrey clarke groves auction, yet runs in P-time. In addition, we show that with proper planning, the D2D Ad stations can be deployed in a manner such that they can fully exploit the spectrum in the subsector formed by the desired cell size. Our proposed framework enables advertisers to indirectly fund the D2D Advertisement service, while also permitting the SP the ability to profit from leasing their unused spectrum to commercial D2D services. [ABSTRACT FROM AUTHOR]

The effort of telecommunications operators in 5G design and implementation is oriented to effective and efficient verticals support. Full network softwarization will deploy tools such as software-defined networks and network functions virtualization to allow dynamic service provisioning on the same physical infrastructure. However, current 5G proposed architecture still requires further enhancement to guarantee full real-time on-demand services. Current virtualization technologies still miss complete automation and adaptation, while they do not have dynamic negotiation capabilities. These issues are bounding the desired complete automation and the significant reduction in OPEX and CAPEX. Thus, this article proposes a full architecture to realize autonomic mobile virtual network operators. These autonomic virtual operators can be deployed by Internet service providers to guarantee efficient and effective network adaptation to unexpected events and real-time resource requests. The objective of an AMVNO is to exploit softwarization of networks and experiential intelligence to play the role of a local operator by performing network management and service release without human intervention. Its autonomic character can also provide proactive actions against unwanted network states. [ABSTRACT FROM AUTHOR]

Wireless network virtualization enables mobile virtual network operators (MVNOs) to develop new services on a low-cost platform by leasing virtual resources from mobile network owners. In this paper, we investigate a two-stage spectrum leasing framework, where an MVNO acquires spectrum resources through both advance reservation and on-demand request. To maximize its surplus, the MVNO needs to jointly optimize the amount of spectrum resources to lease in the two stages by taking into account traffic intensity, random user locations, wireless channel statistics, quality-of-service requirements, and the price differences. Meanwhile, to maximize the utilization of the acquired resources, the MVNO dynamically allocates the spectrum resources to its mobile subscribers (users) according to fast wireless channel fading. We formulate the MVNO’s surplus maximization problem as a tri-level nested optimization problem consisting of dynamic resource allocation (DRA), on-demand request, and advance reservation subproblems. To solve the problem efficiently, we first analyze the DRA problem, and then use the optimal solution to find the optimal leasing decisions in the two stages. In particular, we derive a closed-form expression of the optimal on-demand request, and develop a stochastic gradient descent algorithm to find the optimal advance reservation. For a special case when the proportional fairness utility function is adopted, we show that the optimal two-stage leasing scheme is related to the number of users and is irrelevant to user locations. Simulation results show that the two-stage spectrum leasing scheme can adapt to different levels of traffic and on-demand price variations, and achieve higher surplus than conventional one-stage leasing schemes. [ABSTRACT FROM AUTHOR]

In this paper, we design robust downlink beamforming against the imperfect channel state information (CSI) for beam division multiple access (BDMA) massive multiple-input multiple output (MIMO) systems. Following a worst-case deterministic model, the proposed design is formulated as minimizing the power consumption of base station (BS) under different signal-to-interference-plus-noise ratio (SINR) constraints. The S-Procedure and semi-definite relaxation (SDR) are used to convert the initial non-convex optimization to a convex semi-definite programming problem. Then the optimality of SDR is strictly proved by showing the rank-one property of the optimal beamforming thanks to the orthogonal channels under BDMA scheme. More importantly, we make one step further by deriving the optimal beamforming directions and optimal beamforming power allocation of the SDR in closed-form, which greatly reduces the optimization complexity and makes the proposed design practical for a real word massive MIMO system. Simulation results are then provided to verify the efficiency of the proposed robust beamforming algorithm. [ABSTRACT FROM AUTHOR]

We consider a monitoring application where sensors periodically report data to a common receiver using time division multiplexing. The sensors are constrained by the limited and unpredictable energy availability provided by energy harvesting (EH), and by the channel impairments. To maximize the quality of the reported data, the packets transmitted contain newly generated data blocks together with up to $r - 1$ previously unsuccessfully delivered ones, where $r$ is a design parameter. These data blocks are compressed, concatenated, and encoded with a channel code. The scheme applies lossy compression, such that the fidelity of the individual blocks is traded off with the reliability provided by the channel code. We show that the proposed strategy outperforms the one in which retransmissions are not allowed. We also investigate the tradeoff between the value of $r$ , the compression and the coding rates, under the constraints of the energy availability, and, once $r$ has been decided, use a Markov decision process (MDP) to optimize the compression/coding rates. Finally, we implement a reinforcement learning algorithm, through which devices can learn the optimal transmission policy without knowing a priori the statistics of the EH process, and show that it indeed reaches the performance obtained via MDP. [ABSTRACT FROM AUTHOR]

To achieve spectral-efficient massive access in future wireless networks, this paper proposes a comprehensive fully non-orthogonal communication framework. First, we design a fully non-orthogonal communication scheme which consists of non-orthogonal channel estimation and non-orthogonal multiple access. Then, we analyze the performance of the proposed fully non-orthogonal communication, and derive a tight lower bound on the spectral efficiency in terms of key system parameters and channel conditions. Meanwhile, several novel insights are provided on spectral efficiency via asymptotic analysis in three important cases, i.e., a large number of base station (BS) antennas, a high BS transmit power, and perfect channel state information (CSI) at the BS. Finally, we optimize the performance of the proposed fully non-orthogonal communication and present two simple but efficient optimization algorithms for maximizing the weighted sum of spectral efficiency. Extensive simulation results validate the effectiveness of the proposed schemes. [ABSTRACT FROM AUTHOR]

With the development of smart mobile devices and various mobile applications, content-oriented service has become the most popular service which occupies network resources and results in high traffic load. In order to improve quality of experience in radio access network and reduce the OpEx and CapEx of operators, wireless network virtualization and network slicing come into the vision and are deemed as promising solutions to radio access networks to provide tailored services. Therefore, network slicing and optimization based on content-oriented service become a challenging research direction. In this paper, network slicing and resource optimization on content-oriented application in cache-enabled hybrid radio access network based on complex network are investigated. A Cooperative Network Slicing Framework Based on Content in RAN (CNSC-RAN) is presented. Based on CNSC-RAN, procedures of content-oriented static network slicing and dynamic slicing are proposed. Content-oriented slicing is modeled and analyzed which includes slicing on content cache resources and communication resources. In order to obtain the optimized resources sliced for each content, the optimization problem is formulated to minimize the average system cost to get the contents required by users. The problem is solved by a heuristic algorithm called CCSOA (Content-Centric Slicing Optimization Algorithm) in a dynamic content-oriented network slicing procedure enabling UEs with self-evicting contents. The performance of CCSOA is evaluated by performance metrics including hit rate, average cache occupation, average system cost, and request traffic reduction to macro cell base station comparing with CEE and ProbCache. Simulation results reveal the effectiveness of CCSOA. [ABSTRACT FROM AUTHOR]

Enterprise and Service Provider networks are increasingly making use of Virtualized Network Functions (VNFs) to reap the benefits of reduced Capital expenditures (CAPEX) and Operating expenses (OPEX). Total cost of ownership calculations however are typically a function of the attainable network performance, which in a virtualized system is highly dependent on the overall system architecture and the resource allocation policy. This paper examines how to improve the overall performance of deploying VNFs in a virtualized environment, proposing an appropriate architectural framework to leverage the capabilities of other technologies such as Software Defined Networking (SDN) and Cloud Computing which can be highly complemented with the Network Function Virtualization (NFV) paradigm. We focus on the standardization of the three technologies under a common architecture and we incorporate resource allocation as a main functional architectural block. The problem studied is referred as the VNF placement problem, and tries to efficiently, intelligently, and dynamically allocate a series of VNFs comprising a service chain in a cloud environment according to the current status of the cloud resources. We propose and evaluate a set of algorithms towards satisfying the requirement of enterprise and service providers to grant high performance VNFs for the end users, while allowing the cloud providers to profitably utilize the available resources. [ABSTRACT FROM AUTHOR]

The Software Defined Networking (SDN) architecture was developed in the Open Networking Foundation (ONF) Architecture working group. It is intended to support standardization related to the broader area of software defined networking and affects not only the understanding and related work within ONF, but across a number of standards and/or open-source development organizations. This article provides a brief outline of the SDN architecture, its relation to Network Function Virtualization (NFV) and areas for further study. [ABSTRACT FROM AUTHOR]

Virtual radio access networks (RANs) is the candidate solution for 5G access networks, the concept of virtualised radio resources completing the virtual RAN paradigm. This paper proposes a new analytical model for the management of virtual radio resources in full heterogeneous networks. The estimation of network capacity and data rate allocation are the model's two main components. Based on the probability distribution of the signal-to-interference-plus-noise-ratio observed at the user terminal, the model leads to the probability distribution for the total network data rate. It considers different approaches for the estimation of the total network data rate, based on different channel qualities, i.e., optimistic, realistic and pessimistic. The second component uses the outcome of the first one in order to maximise the weighted data rate subject to the total network capacity, the SLAs (service level agreements) of Virtual Network Operators (VNOs), and fairness. The weights for services in the objective function of the resource allocation component enable the model to have prioritisation among services. The performance of the proposed model is evaluated in a practical heterogeneous access network. Results show an increase of 2.5 times in network capacity by implementing an access point at the centre of each cell of a cellular network. It is shown that the cellular network capacity itself can vary from 0.9 Gbps in the pessimistic approach up to 5.5 Gbps in the optimistic one. Finally, the isolation of service classes and VNOs by means of virtualisation of radio resources is clearly demonstrated. [ABSTRACT FROM AUTHOR]

The heterogeneous cloud radio access network (H-CRAN) is a promising paradigm that integrates the advantages of cloud radio access networks and heterogeneous networks. In this paper, we study joint congestion control and resource optimization to explore the energy efficiency (EE)-guaranteed trade-off between throughput utility and delay performance in a downlink slotted H-CRAN. We formulate the considered problem as a stochastic optimization problem, which maximizes the utility of average throughput and maintains the network stability subject to the required EE constraint and transmit power consumption constraints by traffic admission control, user association, resource block allocation, and power allocation. Leveraging on the Lyapunov optimization technique, the stochastic optimization problem can be transformed and decomposed into three separate subproblems that can be concurrently solved at each slot. The third mixed-integer nonconvex subproblem is efficiently solved by utilizing the continuity relaxation of binary variables and the Lagrange dual decomposition method. Theoretical analysis shows that the proposal can quantitatively control the throughput–delay performance trade-off with the required EE performance. Simulation results consolidate the theoretical analysis and demonstrate the advantages of the proposal from the prospective of queue stability and power consumption. [ABSTRACT FROM PUBLISHER]

In this paper, we propose an architecture of software-defined information-centric network virtualization with device-to-device (D2D) communications, which facilitates dynamic virtual resource allocation and content caching via a software-defined networking (SDN) controller with a global view of the system. In our proposed framework, substrate physical resources can be virtualized and shared among multiple mobile virtual network operators (MVNOs). Meanwhile, by means of integrating D2D communications into information-centric wireless networks, content caching is enabled not only in the air but in mobile devices as well. In addition, taking into consideration inaccurate channel estimation and measurement, we formulate the virtual resource allocation and caching optimization as a discrete stochastic optimization problem in which imperfect channel state information is incorporated. Because the formulated virtual resource allocation problem is a large-scale combinational optimization problem, we exploit discrete stochastic approximation approaches to cope with it. Finally, extensive simulations are conducted to demonstrate the effectiveness of the proposed scheme with different system parameters. Simulation results show that MVNOs can benefit from not only the sharing of physical infrastructure but from the caching functionality that exists in both the air and mobile devices as well. [ABSTRACT FROM PUBLISHER]

Virtualization has been a well-studied topic for traditional servers. As the demand for the support of virtualization on mobile devices emerged, it again became a popular research topic. However, most research work focused on the applications of mobile virtualization. Detailed knowledge of the characteristics of mobile devices is still lacking. In this paper, we focus on the memory management of mobile virtualization, and propose an optimized page translation oPT with hardware/software co-design. The usage pattern of mobile devices is also considered in the design so it is optimal in terms of the hit ratio of the second stage. The variability of translation time in the second stage is eliminated to provide nearly the same behavior as the non-virtualized architecture. We verify the correctness and feasibility of oPT with a formal proof and a comprehensive evaluation based on both software emulation and hardware implementation. The results indicate oPT can outperform the most popular method. The number of memory accesses is reduced by 51.38 to 56.01 percent, and the average translation time is reduced by 78.63 percent. In addition, the power consumption of the hardware unit in oPT is only about one third that of the traditional method. [ABSTRACT FROM AUTHOR]

Mobile users often post nearest neighbor queries based on their current location. Usually, the mobile terminal (user) sends a request to query an untrusted location server, including the position information of the mobile terminal requests, thus leading to the disclosure of one's location. For mobile users providing location services, the privacy of mobile users is crucial. This demand is particularly evident in the mobile network application. According to the structural characteristics of the mobile network, the use of hidden ring and hidden tree can blur mobile subscriber location information in the mobile network and effectively ensure location privacy. This paper proposes a new method of protecting location privacy known as Hidden Ring and Hidden Forest (HRHF), which is the use of breadth-first search to meet certain requirements of the ring and forest in the graph. Based on experimental testing of real and simulated data sets, the HRHF method has demonstrated its effectiveness in protecting location privacy and efficiency in providing quality services. [ABSTRACT FROM AUTHOR]

Virtualization offers significant benefits, such as better isolation and security for mobile systems. However, the limited amount of memory and virtualization’s memory-demanding nature make it challenging to virtualize mobile systems efficiently. In this paper, we utilize morphable resistive memories to design a high-performance mobile system with an extensible memory space. With morphable resistive memories, a simple and effective page management technique, Balloonfish, is proposed to convert the memory cell state between multilevel and single-level for achieving a balance between performance and memory space. First, an application-specific page allocation is proposed for managing morphable resistive memories in virtualized mobile systems. Besides, we use a balloon-style algorithm to balance memory allocation among multiple virtual machines. Our evaluation based on the Samsung Exynos 5250 system-on-chip with various real Android applications shows that our system achieves 28.63% performance improvement compared with the baseline scheme. [ABSTRACT FROM AUTHOR]

Nowadays, sensor-rich smartphones potentially enable the harvesting of huge amounts of valuable sensing data in urban environments, by opportunistically involving citizens to play the role of mobile virtual sensors to cover Smart City areas of interest. This paper proposes an in-depth study of the challenging technical issues related to the efficient assignment of Mobile Crowd Sensing (MCS) data collection tasks to volunteers in a crowdsensing campaign. In particular, the paper originally describes how to increase the effectiveness of the proposed sensing campaigns through the inclusion of several new facilities, including accurate participant selection algorithms able to profile and predict user mobility patterns, gaming techniques, and timely geo-notification. The reported results show the feasibility of exploiting profiling trends/prediction techniques from volunteers' behavior; moreover, they quantitatively compare different MCS task assignment strategies based on large-scale and real MCS data campaigns run in the ParticipAct living lab, an ongoing MCS real-world experiment that involved more than 170 students of the University of Bologna for more than one year. [ABSTRACT FROM AUTHOR]

Bandwidth is an extremely valuable and scarce resource in mobile networks; therefore, efficient mobility-aware bandwidth reservation is necessary to support multimedia applications (e.g., video streaming) that require quality of service (QoS). In this paper, we propose a distributed bandwidth reservation scheme called the mobility-prediction-aware bandwidth reservation (MPBR) scheme. The objective of MPBR is to reduce handoff call dropping rate and maintain acceptable new call blocking rate while providing efficient bandwidth utilization. MPBR consists of 1) a handoff time estimation (HTE) scheme that aims to estimate the time windows when a user will perform handoffs along the path to his destination, 2) an available bandwidth estimation (ABE) scheme that aims to estimate in advance available bandwidth, during the computed time windows in the cells to be traversed by the user to his destination, and 3) an efficient call admission control (ECaC) scheme that aims to control bandwidth allocation in the network cells. The simulation results show that MPBR outperforms existing schemes in terms of reducing handoff call dropping rate. [ABSTRACT FROM PUBLISHER]

Today?s mobile customers desire to remain connected anywhere, at any time, and using any device. This phenomenon has encouraged mobile network operators to build complex network architectures by incorporating new features and extensions, which are harder to manage and operate. In this article we propose a novel and simplified architecture for mobile networks. The proposed architecture, which we call CSDN (Cellular SDN), leverages software defined networking (SDN) and network functions virtualization (NFV). SDN abstracts the network and separates the control plane from the data plane; NFV decouples logical network functions from the underlying hardware, for dynamic resource orchestration. Furthermore, we argue that dynamic resource orchestration and optimal control need real-time context data analyses to make intelligent decisions. Thus, in the proposed architecture we exploit the capability of the mobile edge networks to gather information related to the network as well as the users. This information can be used to optimize network utilization and application performance, and to enhance the user experience. In addition, the gathered data can be shared with third party service providers, enabling the realization of innovative services. [ABSTRACT FROM PUBLISHER]

This article first analyzes the requirements and challenges in the future 5G mobile wireless network. Then the authors describe a new method for radio access technologies called virtual RATs. The proposed scheme can provide a flexible and tailored access network that can meet the requirements and overcome the challenges in mobile broadband networks. The authors also present a high level design of the overall architecture and protocol stack for virtual RATs. Two concepts, virtual RAT Types and interface sets, are introduced. Two essential features, flexible control/user (C/U) plane separation and coordination between virtual RATs, are also discussed. Examples are provided to show how to achieve a flexible and tailored access network for services by using virtual RATs. Finally, the capability of hardware to support implementation of virtual RATs is analyzed. [ABSTRACT FROM PUBLISHER]

HTML5 is an open standard that enables new functionality in the mobile web ecosystem. Speculation by companies around its potential presents an opportunity to view how notions of ‘openness’ are employed to create and support mobile platforms. Particularly, Internet-based companies such as Google seek a foothold in mobile industries which have traditionally been dominated by carriers and device manufacturers. I compare two paradigms of openness and suggest a third in this article.Open sourcedescribes the development of the HTML5 standard by multiple stakeholders in online industries.Open innovationis a process where value is being constantly created and captured, such as when companies make app developer tools public but carefully manage the point-of-sale ‘app stores’. A third type –rhetorical openness– describes claims that strategically bolster a corporate position. Rhetorical openness is increasingly necessary for mobile companies needing to balance multiple stakeholders, appeal to developers, and convince the public of their good intentions. Disputes around the politics of online and mobile media will be increasingly conducted through, using, and around these three forms of openness. [ABSTRACT FROM PUBLISHER]

Abstract: This paper extends previous research examining wholesale market shares of mobile network operators (MNOs). This study demonstrates that wholesale market concentration has decreased over time because of the increase of competition of MNOs for hosting mobile virtual network operators (MVNOs). However, differences in wholesale market shares between MNOs have not disappeared. We propose that those operators that are late entrants in a market and belong to an international group with a proactive attitude towards hosting virtual operators positively influences wholesale market shares of MNOs. The empirical analysis is based on a panel data from 2000 to 2010 corresponding to MNOs and virtual operators in five European countries with high development of the virtual mobile industry. By closely examining KPN we show how being an international mobile group specialising in the wholesale market across Europe has enabled it to exploit complementarities that exist between traditional and virtual businesses. [Copyright &y& Elsevier]

Abstract: A mobile virtual network operator (MVNO) provides mobile telecommunication services by eluding the constraints of the radio communication infrastructure and establishing an agreement with a hosting network operator (HNO) for the use of its spectrum. Thus, MVNOs offer a wide range of mobile services and directly compete with every mobile network operator (MNO). This paper studies the economic justifications for potential regulatory intervention that defines the level of mobile termination rates (MTRs) and negotiations and agreements among MVNOs and HNOs. The results show that symmetric MTR reduction leads to competition growth among operators, forcing every operator to reduce retail prices and, consequently, to enhancing consumer welfare. The paper also finds that a collaborative strategy adopted by an HNO and an MVNO is advantageous for both and induces a reduction in retail prices, thus weakening other MNOs. [Copyright &y& Elsevier]