This paper proposes a reliable data aggregation scheduling that uses caching and re-transmission based on track topology. In the proposed scheme, a node detects packet losses by overhearing messages that includes error indications of the child nodes, from its neighbor nodes. If packet losses are detected, as a backup parent, the node retransmits the lost packet. A retransmission strategy is added into the adaptive timeout scheduling scheme, which adaptively configures both the timeout and the collection period according to the potential level of an event occurrence. The retransmission steps cause an additional delay and power consumption of the sensor nodes, but dramatically increase the data accuracy of the aggregation results. An extensive simulation under various workloads shows that the proposed scheme outperforms other schemes in terms of data accuracy and energy consumption.

Network selection is one of the hot issues in the fusion of heterogeneous wireless networks (HWNs). However, most of previous works only consider selecting single-access network, which wastes other available network resources, rarely take account of multi-access. To make full utilization of available coexisted networks, this paper proposes a novel multi-access selection algorithm based on joint utility optimization for users with multi-mode terminals. At first, the algorithm adopts exponential smoothing method (ESM) to get smoothed values of received signal strength (RSS). Then we obtain network joint utility function under the constraints of bandwidth and number of networks, with the consideration of trade-off between network benefit and cost. At last, Lagrange multiplier and dual optimization methods are used to maximize joint utility. Users select multiple networks according to the optimal association matrix of user and network. The simulation results show that the proposed algorithm can optimize network joint utility, improve throughput, effectively reduce vertical handoff number, and ensure Quality of Service (QoS).

IEEE 802.15.6 provides PHY and MAC layer profiles for wearable and implanted Wireless Body Area Networks (WBANs). The critical requirements of QoS guarantee and ultra-low-power are severe challenges when implementing IEEE 802.15.6. In this paper, the key problem in IEEE 802.15.6 standard that “How to allocate EAP (Exclusive Access Phase)?” is solved for the first time: An analysis of network performance indicates that too much EAP allocation can not promote traffic performance obviously and effectually. However, since EAP allocation plays an important role in guaranteeing quality of service, a customized and quantitative EAP allocation solution is proposed. Simulation results show that the solution can obtain the optimal network performance. Furthermore, the estimated models of delay and energy are developed, which help to design the WBAN according to application requirements and analyze the network performance according to the traffic characteristics. The models are simple, effective, and relatively accurate. Results show that the models have approximated mean and the correlation coefficient is greater than 0.95 compared with the simulations of IEEE 802.15.6 using NS2 platform. The work of this paper can solve crucial practical problems in using IEEE 802.15.6, and will propel WBANs applications widely.

Bandwidth aggregation (BAG) techniques have been researched for many years in an efforts to enhance throughput for multi-homed streaming service. However, despite of the considerable attention being devoted towards energy-efficient communications, the power efficiency for BAG has not been considered yet. To improve the power efficiency in multi-homed streaming service, this paper proposes Power Minimized Rate Allocation Scheme (PMRAS) with optimal rate allocation at each interface while guaranteeing an allowable packet loss rate. In developing PMRAS, we first formulate a power consumption model based on the network interface state (i.e. active and idle state). We adopt a Lagrangian algorithm to solve the convex optimization problem of power consumption. The performance results gained from a numerical analysis and simulations (NS-2) reveal that the proposed scheme offers superior performance over the existing rate allocation scheme for BAG with guaranteed required quality of service.

With the increase of the number of wireless sensing or metering devices, the collection of sensing data using wireless communication becomes an important part of a smart grid system. Cognitive radio technology can be used to facilitate the deployment of smart grid systems. In this paper, we propose a data collection and dissemination framework for cognitive radio smart grid systems to fully utilize wireless resources while maintaining a reliably connected and efficient topology for each channel. In the proposed framework, each sensor node selects a channel considering the primary user (PU) channel utilization and network connectivity. In this way, the data collection and dissemination can be performed with a high reliability and short delay while avoiding a harmful effect on primary users. We use computer simulations to evaluate the proposed framework.

In dense femtocell networks (DFNs), one of the main issues is interference management since interference between femtocell access points (FAPs) reduces the system performance significantly. Further, FAPs serve different numbers of femtocell user equipments (FUEs), i.e., some FAPs have more than one FUE while others have one or no FUEs. Therefore, for DFNs, an intelligent channel assignment scheme is necessary considering both the number of FUEs connected to the same FAPs and interference mitigation to improve system performance. This paper proposes a two-stage dynamic channel assignment (TS-DCA) scheme for downlink DFNs based on orthogonal frequency division multiple access/frequency division duplex (OFDMA/FDD). In stage 1, using graph coloring algorithm, a femtocell gateway (FGW) first groups FUEs based on an interference graph that considers different numbers of FUEs per FAP. Then, in stage 2, the FGW dynamically assigns subchannels to FUE clusters according to the order of maximum capacity of FAP clusters. In addition, FAPs adaptively assign remaining subchannels in FUE clusters to their FUEs in other FUE clusters. Through simulations, we first find optimum parameters of the FUE clustering to maximize the system capacity and then evaluate system performance in terms of the mean FUE capacity, unsatisfied FUE probability, and mean FAP transmission energy consumption according to the different numbers of FUEs and FAPs with a given FUE traffic load.

Researchers have developed several social-based routing protocols for delay tolerant networks (DTNs) over the past few years. Two main routing metrics to support social-based routing in DTNs are centrality and similarity metrics. These two metrics help packets decide how to travel through the network to achieve short delay or low drop rate. This study presents a new routing scheme called Community-Relevance based Opportunistic routing (CROP). CROP uses a different message forwarding approach in DTNs by combining community structure with a new centrality metric called community relevance. One fundamental change in this approach is that community relevance values do not represent the importance of communities themselves. Instead, they are computed for each community-community relationship individually, which means that the level of importance of one community depends on the packet's destination community. The study also compares CROP with other routing algorithms such as BubbleRap and SimBet. Simulation results show that CROP achieves an average delivery ratio improvement of at least 30% and can distribute packets more fairly within the network.

Wireless body area networks (WBANs) have to work with low power and long lifetime to satisfy human biological safety requirements in e-health; therefore extremely low energy consumption is significant for WBANs. IEEE 802.15.6 standard has been published for wearable and implanted applications which provide communication technology requirements in WBANs. In this paper, the cross-layering optimization methodology is used to minimize the network energy consumption. Both the priority strategy and sleep mechanism in IEEE802.15.6 are considered. Macroscopic sleep model based on WBAN traffic priority and microscopic sleep model based on MAC structure are proposed. Then the network energy consumption optimization problem is solved by Lagrange dual method, the master problem are vertically decomposed into two sub problems in MAC and transport layers which are dealt with gradient method. Finally, a solution including self-adaption sleep mechanism and node rate controlling is proposed. The results of this paper indicate that the algorithm converges quickly and reduces the network energy consumption remarkably.

Let T1,T2,...,Tk be spanning trees in a graph G. If, for any two vertices u,v of G, the paths joining u and v on the k trees are mutually vertex-disjoint, then T1,T2,...,Tk are called completely independent spanning trees (CISTs for short) of G. The construction of CISTs can be applied in fault-tolerant broadcasting and secure message distribution on interconnection networks. Hasunuma (2001) first introduced the concept of CISTs and conjectured that there are k CISTs in any 2k-connected graph. Unfortunately, this conjecture was disproved by Péterfalvi recently. In this note, we give a necessary condition for k-connected k-regular graphs with ⌊k/2⌋ CISTs. Based on this condition, we provide more counterexamples for Hasunuma's conjecture. By contrast, we show that there are two CISTs in 4-regular chordal rings CR(N,d) with N=k(d-1)+j under the condition that k ≥ 4 is even and 0 ≤ j ≤ 4. In particular, the diameter of each constructed CIST is derived.

This paper presents a method to seamlessly extend the coverage of energy supply field for wireless sensor networks in order to free sensors from wires and batteries, where the multi-point scheme is employed to overcome path-loss attenuation, while the carrier shift diversity is introduced to mitigate the effect of interference between multiple wave sources. As we focus on the energy transmission part, sensor or communication schemes are out of scope of this paper. To verify the effectiveness of the proposed wireless energy transmission, this paper conducts indoor experiments in which we compare the power distribution and the coverage performance of different energy transmission schemes including conventional single-point, simple multi-point and our proposed multi-point scheme. To easily observe the effect of the standing-wave caused by multipath and interference between multiple wave sources, 3D measurements are performed in an empty room. The results of our experiments together with those of a simulation that assumes a similar antenna setting in free space environment show that the coverage of single-point and multi-point wireless energy transmission without carrier shift diversity are limited by path-loss, standing-wave created by multipath and interference between multiple wave sources. On the other hand, the proposed scheme can overcome power attenuation due to the path-loss as well as the effect of standing-wave created by multipath and interference between multiple wave sources.

With the phenomenal explosion in online services, social networks are becoming an emerging ubiquitous platform for numerous services where service consumers require the selection of trustworthy service providers before invoking services with the help of other intermediate participants. Under this circumstance, evaluation of the trustworthiness of the service provider along the social trust paths from the service consumer to the service provider is required and to this end, selection of the optimal social trust path (OSTP) that can yield the most trustworthy evaluation result is a pre-requisite. OSTP selection with multiple quality of trust (QoT) constraints has been proven to be NP-Complete. Heuristic algorithms with polynomial and pseudo-polynomial-time complexities are often used to deal with this problem. However, existing solutions cannot guarantee the search efficiency, that is, they have difficulty in avoiding suboptimal solutions during the search process. Quantum annealing uses delocalization and tunneling to avoid local minima without sacrificing execution time. Several recent studies have proven that it is a promising way to tackle many optimization problems. In this paper, we propose a novel quantum annealing based OSTP selection algorithm (QA_OSTP) for large-scale complex social networks. Experiments show that QA_OSTP has better performance than its heuristic counterparts.

In mobile wireless sensor networks, coverage and energy are two significant factors determining network performance. When taking both factors into account, the challenges include how to select and migrate nodes to keep coverage quality, how to forecast and prevent potential coverage holes and how to use energy control in mobile networks. In this paper, we propose a new Coverage Maintenance and Energy Control (CMEC) algorithm to achieve and keep high coverage quality and energy efficiency. For CMEC, we provide a new cost metric for selecting migration nodes. Our simulation results confirm that our algorithm improves coverage performance and lifetime of network.

We analyze the outage probability of the multiuser two-way relay network (TWRN) where the N-th best mobile user (MU) out of M MUs and the base station (BS) exchange messages with the aid of an amplify-and-forward relay. In the analysis, we focus on the practical unbalanced Nakagami-m fading between the MUs-relay link and the relay-BS link. We also consider both perfect and outdated channel state information (CSI) between the MUs and the relay. We first derive tight closed-form lower bounds on the outage probability. We then derive compact expressions for the asymptotic outage probability to explicitly characterize the network performance in the high signal-to-noise ratio regime. Based on our asymptotic results, we demonstrate that the diversity order is determined by both Nakagami-m fading parameters, M, and N when perfect CSI is available. When outdated CSI is available, the diversity order is determined by Nakagami-m fading parameters only. In addition, we quantify the contributions of M, N, and the outdated CSI to the outage probability via the array gain.

Time synchronization is important for frequency hopping, power management, scheduling, and basic operations of multi-hop ad-hoc networks. The main problem of existing time synchronization methods is that they depend on a particular node that has the fastest time information among neighbor nodes. The Cucker-Smale flocking model describes that global emergent behavior can be obtained by locally averaging the velocity of each bird. Inspired by this flocking model, we propose a time synchronization method not depending on a particular node. In the proposed method, each node revises its time information via the local-averaging procedure in a distributed manner. A self-correcting procedure is added to the proposed method in order to preserve the effect of time adjustment executed by the local-averaging procedure. The simulation results show that the proposed time synchronization method reduces the time difference among nodes, and enhances the performance of time synchronization in the context of IEEE 802.11-based ad-hoc networks.

High-speed wireless access technologies have evolved over the last years setting new challenges for TCP. That is, to effectively utilize the available network resources and to minimize the effects of wireless channel errors on TCP performance. This paper introduces a new TCP variant, called TCP-BIAD aiming at enhancing TCP performance in broadband wireless access networks. We provide analytical expressions for evaluating the stability, throughput, fairness and friendliness properties of our proposal, and we validate our results by means of computer simulations. Initial results presented in this paper show that this approach achieves high network utilization levels in a wide range of network conditions, while maintaining an adequately fair and friendly behavior with respect to coexisting TCP flows.

Cognitive radio is one of the most promising wireless technologies and has been recognized as a new way to improve the spectral efficiency of wireless networks. In a cognitive radio network, secondary users exchange control information for network coordination such as transmitter-receiver handshakes, for sharing spectrum sensing results, for neighbor discovery, to maintain connectivity, and so on. Spectrum utilization and resource optimizations thus rely on information exchange among secondary users. Normally, secondary users exchange the control information via a predefined channel, called a common control channel (CCC). Most of the medium access control (MAC) protocols for cognitive radio networks were designed by assuming the existence of a CCC, and further assuming that it was available for every secondary user. However, the main drawback of using a static CCC is it is susceptible to primary user activities since the channel can be occupied by primary users at any time. In this paper, we propose a MAC protocol for cognitive radio networks with dynamic control channel assignment, called DYN-MAC. In DYN-MAC, a control channel is dynamically assigned based on spectrum availability. Thus, it can tolerate primary user activities. DYN-MAC also supports collision free network-wide broadcasting and addresses other major problems such as primary/secondary user hidden terminal problems.

Open-access femtocell networks assure the cellular user of getting a better and stronger signal. However, due to the small range of femto base stations (FBSs), any motion of the user may trigger handover. In a dense environment, the possibility of such handover is very frequent. To avoid frequent communication disruptions due to phenomena such as the ping-pong effect, it is necessary to ensure the effectiveness of the cell selection method. Existing selection methods commonly uses a measured channel/cell quality metric such as the channel capacity (between the user and the target cell). However, the throughput experienced by the user is time-varying because of the channel condition, i.e., owing to the propagation effects or receiver location. In this context, the conventional approach does not reflect the future performance. To ensure the efficiency of cell selection, user's decision needs to depend not only on the current state of the network, but also on the future possible states (horizon). To this end, we implement a learning algorithm that can predict, based on the past experience, the best performing cell in the future. We present in this paper a reinforcement learning (RL) framework as a generic solution for the cell selection problem in a non-stationary femtocell network that selects, without prior knowledge about the environment, a target cell by exploring past cells' behavior and predicting their potential future states based on Q-learning algorithm. Then, we extend this proposal by referring to a fuzzy inference system (FIS) to tune Q-learning parameters during the learning process to adapt to environment changes. Our solution aims at minimizing the frequency of handovers without affecting the user experience in terms of channel capacity. Simulation results demonstrate that· our solution comes very close to the performance of the opportunistic method in terms of capacity, while fewer handovers are required on average.· the use of fuzzy rules achieves better performance in terms of received reward (capacity) and number of handovers than fixing the values of Q-learning parameters.

A challenge faced by the video game industry is to develop believable and more intelligent Non-Playable Characters (NPCs). To tackle this problem a low-cost and simple approach has been proposed in this research, which is the development of a gossip virtual social network for NPCs. The network allows simple individual NPCs to communicate their knowledge amongst themselves. The communication within this social network is governed by social-psychological rules. These rules are categorized into four types: Contact, whether the NPC are within a contactable range of each other; Observation, whether the NPCs actually want to talk to each other based on their personal traits; Status, the current representation of the NPCs; and Relationships which determines the long term ties of the NPCs. Evaluations of the proposed gossip virtual social network was conducted, both through statistical analysis and a survey of real users. Highly satisfactory results have been achieved.

This paper studies an underlay-based cognitive two-way relay network which consists of a primary network (PN) and a secondary network (SN). Two secondary users (SUs) exchange information with the aid of multiple single-antenna amplify-and-forward relays while a primary transmitter communicates with a primary receiver in the same spectrum. Unlike the existing contributions, the transmit powers of the SUs and the distributed beamforming weights of the relays are jointly optimized to minimize the sum interference power from the SN to the PN under the quality-of-service (QoS) constraints of the SUs determined by their output signal-to-interference-plus-noise ratio (SINR) and the transmit power constraints of the SUs and relays. This approach leads to a non-convex optimization problem which is computationally intractable in general. We first investigate two necessary conditions that optimal solutions should satisfy. Then, the non-convex minimization problem is solved analytically based on the obtained conditions for single-relay scenarios. For multi-relay scenarios, an iterative numerical algorithm is proposed to find suboptimal solutions with low computational complexity. It is shown that starting with an arbitrarily initial feasible point, the limit point of the solution sequence derived from the iterative algorithm satisfies the two necessary conditions. To apply this algorithm, two approaches are developed to find an initial feasible point. Finally, simulation results show that on average, the proposed low-complexity solution considerably outperforms the scheme without source power control and performs close to the optimal solution obtained by a grid search technique which has prohibitively high computational complexity.

This paper presents a data gathering protocol for wireless sensor network applications that require high throughput and topology adaptability under the premises of uniform traffic and energy-rich environments. Insofar as high throughput is concerned, TDMA is more suitable than CSMA. However, traditional TDMA protocols require complex scheduling of transmission time slots. The scheduling burden is the primary barrier to topology adaptability. Under the premises of uniform traffic and energy-rich environments, this paper proposes a token-scheduled multi-channel TDMA protocol named TKN-TWN to ease the scheduling burden while exploiting the advantages of TDMA. TKN-TWN uses multiple tokens to arbitrate data transmission. Due to the simplified scheduling based on tokens, TKN-TWN is able to provide adaptability for topology changes. The contention-free TDMA and multi-channel communication afford TKN-TWN the leverage to sustain high throughput based on pipelined packet forwarding. TKN-TWN further associates the ownership of tokens with transmission slot assignment toward throughput optimization. We implement TKN-TWN on Tmote Sky with TinyOS 2.1.1 operating system. Experimental results in a deployed network consisting of 32 sensor nodes show that TKN-TWN is robust to network changes caused by occasional node failures. Evaluation also shows that TKN-TWN is able to provide throughput of 9.7KByte/s.