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In task offloading systems, it is imperative to guarantee that an offloaded task is completed within a pre-specified deadline. In this paper, we propose a distributed device-to-device (D2D) offloading system (DDOS) in which a task owner opportunistically broadcasts an offloading request that includes its mobility level and task completion deadline. After receiving the request, mobile devices in the vicinity of the task owner employ a constraint stochastic game to decide, in a distributed manner, whether to accept the request or not. We devise a best response dynamics-based algorithm (BRDA) to obtain a multi-policy constrained Nash equilibrium. Evaluation results demonstrate that DDOS can guarantee a high on-time task completion probability, as well as a low energy consumption.

In device-to-device (D2D) offloading, frequent offloading to a specific mobile device (i.e., an offloadee) can violate the privacy of a task owner and proper offloading results cannot always be guaranteed due to untruthful mobile devices. To address these problems, we propose a privacy-preserving and trustworthy D2D offloading scheme (PPTS) with two steps: 1) a privacy-preserving offloading step and 2) a blockchain-based verification step. In the first step, a task owner selects several offloadees and offloads the tasks redundantly to them to obtain reliable offloading results with a minimum task completion delay while preserving its own privacy at a sufficient level. In addition, the task owner chooses another mobile device as a verifier. In the second step, the task owner and verifier exploit blockchain networks to check whether the offloading results are appropriately processed. We formulate a static game to decide an appropriate redundancy ratio of offloading tasks and incentives for the offloadees.The evaluation results demonstrate that PPTS can provide reliable offloading results with a reduced task completion delay and guarantee a sufficient level of privacy of the task owner.

In energy harvesting Internet of Things (IoT) systems, the age of information (AoI) should be maintained at a low level to guarantee the accuracy and reliability of derived decisions. In this paper, we design an information freshness-guaranteed and energy-efficient data generation control system (IFE-DGCS) where an IoT gateway with a directional antenna determines the polling frequency for each sector by selecting a polling sector at periodic decision epochs. When polling data, the IoT gateway transfers the RF energy to IoT devices in the polling sector by means of simultaneous wireless information and power transfer (SWIPT). To minimize the energy outage probability while maintaining the AoI below a certain level, a constrained Markov decision process (CMDP) is formulated and the optimal stochastic policy on the polling sector is obtained by a linear programming (LP). To resolve the curse of the dimensionality problem in CMDP, a greedy IFE-DGCS is developed and its performance is extensively studied. Evaluation results demonstrate that IFE-DGCS with the optimal policy achieves a comparable energy outage probability to the conventional energy-oriented scheme while guaranteeing a sufficiently low AoI.

In environmental monitoring systems, unnecessary transmissions can occur when an Internet of Things (IoT) device transmits its data without any consideration on neighbors’ transmissions. In this paper, we propose a neighbor-aware energy-efficient monitoring system (NA-EEMS) for energy harvesting IoT devices. In NA-EEMS, to exploit spatial correlation among IoT devices, geographically proximate IoT devices transmit their sensed data in a distributed manner by means of a constraint stochastic game. We devise a best response dynamics-based algorithm to obtain a multipolicy constrained Nash equilibrium. Evaluation results demonstrate that NA-EEMS can improve the network lifetime while preserving the monitoring probability above a desired level.

In data acquisition (DAQ)-based services of Internet of things (IoT), IoT devices sense and transmit data to the application server through IoT gateway (GW). Due to the energy limitation of IoT devices, it is important to increase their energy efficiency. Further, when data from a very large number of IoT devices is individually transmitted, the data traffic volume can be significant. To resolve these issues, IoT devices and IoT GW can use sleep mode and data aggregation, respectively. However, when the IoT devices are in sleep mode for a long time and/or data are aggregated in IoT GW for a long time without any transmissions, data can become inconsistent. In this paper, we propose a consistency-guaranteed and energy efficient sleep scheduling algorithm (CG-E2S2) with data aggregation. In CG-E2S2, the optimal sleep duration of IoT devices and aggregation duration in IoT GW are jointly determined by means of a Markov decision process (MDP) with the consideration of energy efficiency of IoT devices, data traffic in networks, and data consistency. The evaluation results demonstrate that CG-E2S2 with the optimal policy outperforms the comparison schemes in terms of energy efficiency, data traffic volume, and data consistency.

Cloud storage applications, such as Dropbox and Google Drive, have recently become very popular among mobile users. In these applications, a cloud server is responsible for synchronizing updates to files among mobile users, and thus if files are shared by many mobile users and are frequently updated then the resulting synchronization traffic can be significant. In order to reduce the synchronization traffic with providing acceptable access latency, we propose a fog-assisted aggregated synchronization (FAS) scheme in which the fog computing server and the cloud server conduct localized and aggregated synchronizations, respectively. We develop an analytical model of the FAS scheme based on renewal-reward theory and use it for model-based adjustment of the timer that controls the trade-off between access latency and synchronization traffic. We use analytical and simulation results to give insight into the effects of the timer, the update-to-access ratio, the number of mobile users, and the sensitivity to the arrival process. The analytical and simulation results demonstrate that the FAS scheme can reduce the synchronization traffic significantly with acceptable access latency compared to conventional schemes.

Recently, the interest in operating long term evolution (LTE) in unlicensed bands (i.e., LTE-U) has increased. However, since LTE does not sense for channel vacancy prior to transmissions, whereas a wireless local area network (WLAN) is based on carrier sensing multiple access, LTE interference severely degrades the performance of WLAN. To maximize the LTE throughput while maintaining fairness between LTE and WLAN, we formulate a joint optimization problem of channel selection and frame scheduling in LTE. As a practical solution of this problem, we propose a low-complexity heuristic algorithm called the sequential operation algorithm (SOA). Evaluation results demonstrate that SOA can achieve an LTE throughput comparable to that of the optimal solution, while maintaining fairness between LTE and WLAN by selecting appropriate channels and conducting effective frame scheduling.

Recently, femtocells are widely deployed to offload the traffic from the macrocell. Since conventional location management schemes of femto/macrocell networks do not consider mobility pattern of the mobile node (MN), unnecessary location updates can occur. Specifically, when an MN moves along the contour of the femtocell coverage, the MN frequently executes location update procedures, which causes significant location update cost. To address this problem, we propose a mobility-aware location management (MALM) scheme, where the MN conducts location update only at specific femtocells in which it is expected that the MN stays for a long time. To optimize MALM, a Markov decision process (MDP) problem is formulated and the optimal policy is determined. Evaluation results demonstrate that MALM with the optimal policy can reduce the number of location updates while providing sufficient offloading gain.

In the delayed WiFi offloading, since data are downloaded only through WiFi networks before a predefined delay timer expires, the performance of the delayed WiFi offloading is affected by the delay timer value. To assess the performance of the delayed WiFi offloading, we develop analytical models for the expected saving monetary cost and download completion time. Based on these analytical models, the optimal delay timer is derived to maximally save the monetary cost while maintaining the outage probability on the download time at low level. Evaluation results demonstrate the effects of the average cellular-only residence time and WiFi data rate, and show that better performance can be achieved when the delay timer is set to the optimal value.

Article synchronization is one of the most fundamental issues in online social networking services (SNSs). In particular, when deploying multiple access networks with different transmission costs, an efficient synchronization scheme should be devised for users to enjoy SNSs in heterogeneous wireless networks. In this paper, we propose an opportunistic push scheme (OPS) that aggregates published articles, opportunistically pushing them through low-cost access networks (e.g., open Wi-Fi networks). To balance the reduced transmission costs and the increased page loading time, we formulate a Markov decision process problem that considers a mobility model based on the users’ social contact pattern. Evaluation results demonstrate that OPS with the optimal policy can reduce the number of transmissions in high-cost access networks, while satisfying users’ quality of experience in terms of the page loading time.

In cloud storage applications where the data is shared by multiple mobile users, it is essential to provide the consistency among mobile users by means of appropriate synchronization algorithms. In particular, if the data is frequently updated and the number of mobile users sharing the data is large, the synchronization traffic can be significant. Moreover, the excessive synchronization traffic in mobile networks is more important in terms of radio resource utilization and energy consumption. In this paper, we propose an efficient delta synchronization (EDS) algorithm that aggregates the updated data to reduce the synchronization traffic and synchronizes the aggregated one periodically to satisfy the consistency. To find out the optimal policy for the aggregation and the periodical synchronization, an optimization problem is formulated as a Markov decision process (MDP) and a value iteration algorithm is presented for computing the stationary deterministic policy. Numerical results demonstrate that EDS can choose the optimal action that strikes a balance between the reduction of the synchronization traffic and the satisfaction of the consistency.

International audience; Network mobility basic support (NEMO-BS) supports efficient group mobility. However, when NEMO-BS is applied to public transportation systems where mobile nodes (MNs) frequently get in/off the public transportation, significant signaling overhead owing to frequent and unnecessary binding updates can occur. To address this problem, we propose a delayed location management (DLM) scheme where an MN postpones its binding update for a pre-defined timer to mitigate the binding update overhead. To evaluate the performance of DLM, we develop an analytical model for the binding update cost and the packet delivery cost during the boarding time. Also, a timer selection algorithm is proposed to optimize the performance of DLM. Evaluation results demonstrate that DLM can reduce the binding update cost and packet delivery cost in a balanced manner by choosing an appropriate timer.

Recently, there has been an increasing interest in operating long-term evolution (LTE) in unlicensed bands (i.e., LTE-U). However, since LTE and wireless local area networks (WLANs) are designed to operate in different bands, they have no coexistence mechanism, which leads to significant performance degradation. In particular, since LTE does not sense channel vacancy prior to transmissions, the LTE interference severely affects the WLAN operation. To address this problem, we propose a fair listen-before-talk (F-LBT) algorithm for coexistence of LTE-U and WLAN in unlicensed bands. F-LBT jointly considers the total system throughput and the fairness between LTE-U and WLAN and then allocates an appropriate idle period for WLAN. Evaluation results demonstrate that F-LBT can improve the total system throughput while providing the fairness between LTE-U and WLAN.

Long-term evolution (LTE)/LTE-advanced (LTE-A) networks have recently introduced a data packet forwarding scheme between evolved node Bs (eNBs) to reduce the signaling overhead and the delay incurred in the data path switching scheme, which is a baseline handover scheme in LTE/LTE-A networks. Even with the data packet forwarding scheme, if the length of the forwarding chain is set inappropriately, the data packet forwarding scheme suffers from the degraded throughput. To attain the optimal handover performance in terms of throughput and delay and reduce the signaling overhead, we propose an optimized and distributed data packet forwarding scheme where the optimal length of the forwarding chain is obtained by a Markov decision process (MDP). In addition, a low-complexity value iteration algorithm is devised to solve the optimality equation of MDP in a more practical manner. Real trace-driven evaluation results demonstrate that the proposed scheme determines the optimal length of the forwarding chain adaptively to the applications' quality-of-service (QoS) requirements and reduces the signaling overhead and delay while achieving higher throughput in diverse environments.

WiFi offloading is a promising technique for addressing the mobile data explosion problem. In this paper, we consider two types of WiFi offloading techniques: 1) opportunistic WiFi offloading, where data offloading is conducted only when a mobile node opportunistically meets WiFi access points (APs); and 2) delayed WiFi offloading, where data transfer is delayed with the expectation of future AP contacts. We developed analytical models on WiFi offloading efficiency, which is defined as the ratio of the amount of offloaded data to the total amount of data. Extensive simulation results are given to validate the analytical models and to demonstrate the effects of the average cellular residence time, the delay bound, the variability of the WiFi residence time, the WiFi data rate, and the average session duration on WiFi offloading efficiency.

Distributed mobility management (DMM) is a promising technology to address the mobile data traffic explosion problem. Since the location information of mobile nodes (MNs) are distributed in several mobility agents (MAs), DMM requires an additional mechanism to share the location information of MNs between MAs. In the literature, multicast or distributed hash table (DHT)-based sharing methods have been suggested; however they incur significant signaling overhead owing to unnecessary location information updates under frequent handovers. To reduce the signaling overhead, we propose a timer-based Bloom filter aggregation (TBFA) scheme for distributing the location information. In the TBFA scheme, the location information of MNs is maintained by Bloom filters at each MA. Also, since the propagation of the whole Bloom filter for every MN movement leads to high signaling overhead, each MA only propagates changed indexes in the Bloom filter when a pre-defined timer expires. To verify the performance of the TBFA scheme, we develop analytical models on the signaling overhead and the latency and devise an algorithm to select an appropriate timer value. Extensive simulation results are given to show the accuracy of analytical models and effectiveness of the TBFA scheme over the existing DMM scheme.

In this paper, we propose a novel session-initiation-protocol-based location management framework in opportunistic WiFi networks. In the proposed framework, a mobile terminal needs to update its attachment to the network only when it connects to a new WiFi access point to reduce its location update traffic. In addition, to find out the exact point of attachment, a timer-based session setup procedure is introduced, which can intelligently reduce the session setup latency by looking for a user in either WiFi or cellular systems. We develop analytical models for the location update cost and the session setup latency and investigate the optimization of the timer under the realistic WiFi hotspot residence time model.

In this paper, we propose a vehicular passenger mobility-aware bandwidth allocation (V-MBA) scheme in mobile hotspots. The V-MBA scheme consists of both call admission control and bandwidth adjustment functions to lower handoff vehicle service dropping probability and efficiently utilize resource of base station. Specifically, a handoff priority scheme with guard bandwidth is employed to protect handoff vehicle service. Also, bandwidth is dynamically assigned to each vehicle by exploiting vehicular passenger movement pattern that includes getting on and off events at a station. We evaluate the V-MBA scheme by developing a continuous-time Markov chain model. Simulation results demonstrate that the V-MBA scheme can guarantee low new vehicle service blocking probability and handoff vehicle service dropping probability through flexible bandwidth allocation.

In this paper, we propose a mobility-aware call admission control (MA-CAC) algorithm with a handoff queue (HQ) in mobile hotspots, where different admission control policies are employed, depending on the vehicle mobility. Specifically, when a vehicle is static, a handoff priority scheme with guard channels is studied to protect vehicular handoff users because handoff users may get on the vehicle. In addition, an HQ is examined during stopping to further accept handoff users. On the other hand, for a moving vehicle, no guard channels for handoff users are allocated to maximize channel utilization. By means of Markov chains, we evaluate MA-CAC with an HQ in terms of new-call blocking probability (NCBP), handoff-call dropping probability (HCDP), handoff-call waiting time in the HQ, and channel utilization. Analytical and simulation results demonstrate that MA-CAC with an HQ can lower both the HCDP and the NCBP while maintaining high channel utilization.

Distributed mobility management (DMM) is an attractive approach to address the mobile traffic explosion problem, and thus it is perceived as a promising technology for mobility management in 5G. In this paper, we propose a software-defined networking (SDN) approach for DMM (denoted by SDN-DMM). Unlike the existing approaches for DMM (i.e., network-based or terminal-based), SDN-DMM implements the location and handover management functions at the centralized SDN controller while the packet forwarding function is fully distributed at access routers. Therefore, SDN-DMM can achieve the packet forwarding path optimization and provide significant benefits in terms of network and traffic management.

Conference of 12th EAI International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, QShine 2016 ; Conference Date: 7 July 2016 Through 8 July 2016; Conference Code:196279; International audience; Network mobility basic support (NEMO-BS) supports efficient group mobility. However, when NEMO-BS is applied to public transportation systems where mobile nodes (MNs) frequently get in/off the public transportation, significant signaling overhead owing to frequent and unnecessary binding updates can occur. To address this problem, we propose a delayed location management (DLM) scheme where an MN postpones its binding update for a pre-defined timer to mitigate the binding update overhead. To evaluate the performance of DLM, we develop an analytical model for the binding update cost and the packet delivery cost during the boarding time. Evaluation results demonstrate that DLM can reduce the binding update cost and packet delivery cost by choosing an appropriate timer.

In service function chaining (SFC), an ordered list of service functions (SFs) is specified for network services, and those SFs should be placed in appropriate service nodes (SNs) to satisfy the given service latency requirement. In this paper, we formulate an integer non-linear programming (INLP) problem for the optimal placement of SFs when the latency requirement for network services and network conditions (e.g., link latency and SN capacity) are given. Evaluation results show that the optimal placement can achieve lower latency than conventional schemes.

Nowadays, online social networking services in wireless networks are very popular. In this paper, we propose a timer-based push scheme (TPS) where a number of articles posted during a pre-defined time interval are pushed to users and thus the number of push operations and articles to be pulled can be reduced. We develop an analytical model for TPS and derive the optimal timer minimizing the total cost. Simulation results are given to show the effectiveness of TPS over the existing push N scheme and to validate the analytical results.

Recently, there is an increasing interest for operating long term evolution (LTE) in unlicensed bands (i.e., LTE-U). Up to date, only a few studies have been reported to show the performance of LTE-U. In this work, we first modify the LENA LTE module in the ns-3 simulator and present extensive simulation results in terms of TCP goodput under LTE-U handover scenarios. Simulation results reveal that a new TCP mechanism is needed for coexistence between LTE-U and LTE.

Current evolved packet core (EPC) systems in LTE/LTE-A networks suffer from the exponentially increased mobile traffic and thus research on new EPC architectures is ongoing. In this paper, we introduce a virtualized EPC (vEPC) system where middlebox functions of the existing EPC systems are implemented in virtualized software modules and the virtualized software modules operate over selected physical service nodes. To minimize the impact of the increased transmission cost in vEPC, the optimal placement of middlebox functions is also investigated. Numerical results demonstrate that the proposed scheme can achieve lower packet transmission cost than the conventional one.

Recently, the femtocell has been proposed to offload the traffic from the macrocell. In femto/macrocell networks, a location management should be supported to keep track of the current location of a mobile node (MN). Since the conventional mobility management scheme of femto/macrocell networks does not consider mobility pattern of the MN, unnecessary location updates occur. Specifically, when the MN moves along the contour of the femtocell coverage, the MN frequently executes location update which causes high location update cost. To address this problem, we propose a mobility-aware location management (MALM) scheme that the MN does not execute location update in femtocells where the MN stops by while conducting location update at the specific locations expected that the MN stays for a long time. Then, to optimize MALM, a Markov decision process (MDP) problem is formulated and the optimal policy is determined. Evaluation results demonstrate that MALM with the optimal policy can reduce the number of location updates and provide sufficient offloading effect.

For multimedia streaming in mobile environments, video bitrate should be carefully determined and different channel quality and pricing in heterogeneous wireless networks (e.g., cellular and WiFi networks) need to be considered. In this work, we propose a new bitrate adaptation (BA) technique called mobility-aware dynamic adaptive streaming over HTTP (MDASH), in which a cellular data usage is minimized through a Markov Decision Process (MDP) framework. Preliminary simulation results are shown that MDASH can reduce 23% of the cellular data usage without any playback interruptions while minimizing the temporal variations in the video quality.

The article synchronization is one of the most fundamental issues in online social networking services. In particular, an efficient synchronization scheme should be devised when users enjoy online social networking services in heterogeneous wireless networks where multiple access networks with different transmission costs are deployed. In this paper, we propose an opportunistic push scheme (OPS) that aggregates the published articles and pushes opportunistically the aggregated articles through low-cost access networks (e.g., open WiFi networks). To balance the reduced transmission cost and the consistency of articles, a Markov decision process (MDP) problem is formulated and the optimal policy is determined. Numerical results demonstrate that OPS with the optimal policy can reduce the number of transmissions in high-cost access networks while satisfying users' quality of experience (QoE) in terms of the article consistency.

Contents oriented network (CON) is a new network paradigm to redesign Internet for providing enhanced user experience in contents delivery services. In this paper, we introduce a cross layer approach to reduce the contents access latency when CON is deployed in mobile environments. The proposed scheme can be easily implemented by means of IEEE 802.21 media independent handover (MIH) and can reduce the contents access latency significantly.

In home networks, a variety of smart devices are connected to a WiFi access point (AP) and the oversized buffer of the AP causes high latency/delay jitter and reduced network throughput (known as the bufferbloat problem). To mitigate this problem, appropriate active queue management (AQM) algorithms should be implemented at the AP. In this paper, we conduct extensive simulation study on the performance of CoDel, which is one of the most effective AQMs. Simulation results demonstrate that CoDel with carefully configured parameters can provide comparable throughput and shorter round-trip time compared to the tail drop queue management algorithm.

Recently, a data packet forwarding scheme between evolved node Bs (eNBs) in long-term evolution (LTE)/LTE-advanced (LTE-A) networks has been proposed to reduce the signaling overhead and delay incurred in the data path switching scheme. However, the conventional data packet forwarding scheme suffers from the increased delay when the length of the data packet forwarding chain is inappropriately long. To attain the optimal handover performance in LTE/LTE-A networks, we propose an optimized and distributed data packet forwarding scheme where an optimal length of the forwarding chain is obtained by a Markov decision process (MDP). Numerical results demonstrate that the proposed scheme achieves the optimal and adaptive performance in diverse network environments.

Recently distributed mobility management (DMM) in ID/locator separation architectures has been widely investigated to provide load balanced and scalable mobility services. However, it has drawbacks in terms of the network mobility (NEMO) support since IDs cannot be aggregated. In this paper, a novel network mobility support protocol is proposed in a distributed ID/locator separation architecture. In the proposed protocol, a mobile router sends an aggregate location update message on the behalf of multiple mobile nodes and thus the signaling overhead and delay can be significantly reduced.

Contents oriented networking (CON) is an emerging concept, in which a new networking paradigm based on contents name instead of host address is introduced. For gradual deployment towards CON from legacy Internet, an interworking architecture between CON and Internet is indispensible. In this paper, we introduce the proxy name server (PNS) that performs contents name from/to host address translation for interworking. We first present the PNS structure and detailed interworking operations. Also, further considerations for building better interworking architecture are discussed.

An ID/locator separation architecture is one of the most recognized technologies for Future Internet. In ID/locator separation architectures, an ID/locator mapping system is indispensable to provide location management in mobile environments. This paper conducts a comparative study on two approaches, centralized and distributed, for building ID/locator mapping systems. We develop analytical models on the signaling cost incurred in location update and location query procedures in centralized and distributed ID/locator mapping systems. We conduct extensive numerical analysis over mesh and tree topologies. Numerical results demonstrate that the distributed ID/locator mapping system with distributed hash table (DHT) has comparable signaling cost to the centralized ID/locator mapping system while providing higher scalability and robustness.

Nowadays, online social networking services are very popular. In this paper, we conduct a comparative study of two push schemes in online social networking services: timer-based push scheme (TPS) and push N scheme (PNS). Simulation results demonstrate that TPS has comparable performance to PNS and TPS is more friendly to implementations.