In communication networks, congestion control, routing, and multiple access schemes for scheduling transmissions are typically regulated by distributed algorithms. Engineers designed these algorithms using clever heuristics that they refined in the light of simulation results and experiments. Over the last two decades, a deeper understanding of these algorithms emerged through the work of researchers. This understanding has a real potential for improving the design of protocols for data centers, cloud computing, and even wireless networks. Since protocols tend to be standardized by engineers, it is important that they become familiar with the insights that emerged in research. We hope that this paper might appeal to practitioners and make the research results intuitive and useful. The methods that the paper describes may be useful for many other resource allocation problems such as in call centers, manufacturing lines, hospitals and the service industry.

Nature-inspired devices and architectures are attracting considerable attention for various purposes, including the development of novel computing techniques based on spatiotemporal dynamics, exploiting stochastic processes for computing, and reducing energy dissipation. This paper demonstrates that networks of optical energy transfers between quantum nanostructures mediated by optical near-field interactions occurring at scales far below the wavelength of light could be utilized for solving a constraint satisfaction problem (CSP), the satisfiability problem (SAT), and a decision making problem. The optical energy transfer from smaller quantum dots to larger ones, which is a quantum stochastic process, depends on the existence of resonant energy levels between the quantum dots or a state-filling effect occurring at the larger quantum dots. Such a spatiotemporal mechanism yields different evolutions of energy transfer patterns in multi-quantum-dot systems. We numerically demonstrate that networks of optical energy transfers can be used for solution searching and decision making. We consider that such an approach paves the way to a novel physical informatics in which both coherent and dissipative processes are exploited, with low energy consumption.

In this paper, we briefly review the scheme of counting statistics, in which a probability of the number of monitored or target transitions in a Markov jump process is evaluated. It is generally easy to construct a master equation for the Markov jump process, and the counting statistics enables us to straightforwardly obtain basic equations of the counting statistics from the master equation; the basic equation is used to calculate the cumulant generating function of the probability of the number of target transitions. For stationary cases, the probability is evaluated from the eigenvalue analysis. As for the nonstationary cases, we review a numerical integration scheme to calculate the statistics of the number of transitions.

The relationship between different brain areas is characterized by functional networks through correlations of time series obtained from neuroimaging experiments. Due to its high spatial resolution, functional MRI data is commonly used for generating functional networks of the entire brain. These networks are comprised of the measurement points/channels as nodes and links are established if there is a correlation in the measured time series of these nodes. However, since the evaluation of correlation becomes more accurate with the length of the underlying time series, we construct in this paper functional networks from MEG data, which has a much higher time resolution than fMRI. We study in particular how the network topologies change in an experiment on ambiguity of words, where the subject first receives a priming word before being presented with an ambiguous or unambiguous target word.

We propose a natural synchronization scheme for wireless uncoupled devices, without any signal exchange among them. Our proposed scheme only uses natural environmental fluctuations, such as the temperature or humidity of the air, the environmental sounds, and so on, for the synchronization of the uncoupled devices. This proposed synchronization is realized based on the noise-induced synchronization phenomenon, uncoupled nonlinear oscillators synchronize with each other only by adding identical common noises to each of them. Based on the theory of this phenomenon, the oscillators can also be synchronized by noise sequences, which are not perfectly identical signals. Since the environmental natural fluctuations collected at neighboring locations are similar to each other and cross-correlation becomes high, our proposed scheme enabling synchronization only by natural environmental fluctuations can be realized. As an application of this proposed synchronization, we introduce wireless sensor networks, for which synchronization is important for reducing power consumption by intermittent data transmission. We collect environmental fluctuations using the wireless sensor network devices. Our results show that the wireless sensor network devices can be synchronized only by the independently collected natural signals, such as temperature and humidity, at each wireless sensor device.

Network tomography is a technique for estimating internal network characteristics from end-to-end measurements. In this paper, we focus on loss tomography, which is a network tomography problem for estimating link loss rates. We study a loss tomography problem to detect links with high link loss rates in network environments with dynamically changing link loss rates, and propose a window-based sequential loss tomography scheme. The loss tomography problem is formulated as an underdetermined linear inverse problem, where there are infinitely many candidates of the solution. In the proposed scheme, we use compressed sensing, which can solve the problem with a prior information that the solution is a sparse vector. Measurement nodes transmit probe packets on measurement paths established between them, and calculate packet loss rates of measurement paths (path loss rates) from probe packets received within a window. Measurement paths are classified into normal quality and low quality states according to the path loss rates. When a measurement node finds measurement paths in the low quality states, link loss rates are estimated by compressed sensing. Using simulation scenarios with a few link states changing dynamically from low to high link loss rates, we evaluate the performance of the proposed scheme.

The link structure of the Web is generally viewed as a webgraph. One of the main objectives of web structure mining is to find hidden communities on the Web based on the webgraph, and one of its approaches tries to enumerate substructures, each of which corresponds to a set of web pages of a community or its core. Research has shown that certain substructures can find sets of pages that are inherently irrelevant to communities. In this paper, we propose a model, which we call contracted webgraphs, where such substructures are contracted into single nodes to hide useless information. We then try structure mining iteratively on those contracted webgraphs since we can expect to find further hidden information once irrelevant information is eliminated. We also explore the structural properties of contracted webgraphs from the viewpoint of scale-freeness, and we observe that they exhibit novel and extreme self-similarities.

Computing the level of trust between two indirectly connected users in an online social network (OSN) is a problem that has received considerable attention of researchers in recent years. Most algorithms focus on finding the most accurate prediction of trust; however, little work has been done to make them fast enough to be applied on today's very large OSNs. To address this need we propose a method for fast trust computation that is suitable for very large social networks. Our method uses min-max trust propagation strategies along with the landmark based method. Path strength of every node is pre-computed to and from a small set of reference users or landmarks. Using these pre-computed values, we estimate the strength of trust paths from the source user to in-neighbors of the target user. The final trust estimate is obtained by aggregating information from most reliable in-neighbors of the target user. We also describe how the landmark based method can be used for fast trust computation according to other trust propagation models. Experiments on a variety of real social network datasets verify the efficiency and accuracy of our method.

Source routing multicast has been gathering much more attention rather than traditional IP multicast, since it is thought to be more scalable in terms of the number of groups at the cost of higher traffic loads. This paper introduces a mathematical framework to analyze the scalability of source routing multicast and IP multicast by leveraging previous multicast studies. We first analyze the amount of data traffic based on the small-world nature of networks, and show that source routing multicast can be as efficient as IP multicast if a simple header fragmentation technique (subgrouping) is utilized. We also analyze scalability in terms of group numbers, which are derived under the equal budget assumption. Our analysis shows that source routing multicast is competitive for low bit-rate streams, like those in the publish/subscribe service, but we find some factors that offset the advantage. This is the first work to analytically investigate the scalability of source routing multicast.

Machine-to-Machine (M2M) communication is expected to grow in networks of the future, where massive numbers of low cost, low function M2M terminals communicate in many-to-many manner in an extremely mobile and dynamic environment. We propose a network architecture called Data-centric Network (DCN) where communication is done using a data identifier (ID) and the dynamic data registered by mobile terminals can be retrieved by specifying the data ID. DCN mitigates the problems of prior arts, which are large size of routing table and transaction load of name resolution service. DCN introduces concept of route attraction and aggregation in which the related routes are attracted to an aggregation point and aggregated to reduce routing table size, and route optimization in which optimized routes are established routes to reduce access transaction load to the aggregation points. These allow the proposed architecture to deal with ever increasing number of data and terminals with frequent mobility and changes in data.

LT codes are the first practical rateless codes whose reception overhead totally depends on the degree distribution adopted. The capability of LT codes with a particular degree distribution named robust soliton has been theoretically analyzed; it asymptotically approaches the optimum when the message length approaches infinity. However, real applications making use of LT codes have finite number of input symbols. It is quite important to refine degree distributions because there are distributions whose performance can exceed that of the robust soliton distribution for short message length. In this work, a practical framework that employs evolutionary algorithms is proposed to search for better degree distributions. Our experiments empirically prove that the proposed framework is robust and can customize degree distributions for LT codes with different message length. The decoding error probabilities of the distributions found in the experiments compare well with those of robust soliton distributions. The significant improvement of LT codes with the optimized degree distributions is demonstrated in the paper.

A mobile hotspot is a moving vehicle that hosts an Access Point (AP) such as train, bus and subway where users in these vehicles connect to external cellular network through AP to access their internet services. To meet Quality of Service (QoS) requirements, typically throughput and/or delay, a Call Admission Control (CAC) is needed to restrict the number of users accepted by the AP. In this paper, we analyze a modified guard channel scheme as CAC for mobile hotspot as follows: During a mobile hotspot is in the stop-state, we adopt a guard channel scheme where the optimal number of resource units is reserved for vertical handoff users from cellular network to WLAN. During a mobile hotspot is in the move-state, there are no handoff calls and so no resources for handoff calls are reserved in order to maximize the utility of the WLAN capacity. We model call's arrival and departure processes by Markov Modulated Poisson Process (MMPP) and then we model our CAC by 2-dimensional continuous time Markov chain (CTMC) for single traffic and 3-dimensional CTMC for two types of traffic. We solve steady-state probabilities by the Quasi-Birth and Death (QBD) method and we get various performance measures such as the new call blocking probabilities, the handoff call dropping probabilities and the channel utilizations. We compare our CAC with the conventional guard channel scheme which the number of guard resources is fixed all the time regardless of states of the mobile hotspot. Finally, we find the optimal threshold value on the amount of resources to be reserved for the handoff call subject to a strict constraint on the handoff call dropping probability.

Conventional CPM signals employ information sequence with time-unlimited phase shaping pulse (PSP) to achieve power and bandwidth efficient transmission. On the contrary, information sequence using time-limited PSP was believed to produce power-wasting data-independent discrete spectral lines in CPM spectra, and was suggested to be avoided. In this paper, we revisit this problem and adopt the time-limited PSP to replace the one with time-unlimited, it turns out to have an alternative solution to the CPM scheme. We first modify the spectral computing formula for the CPM with time-limited PSP (or CPM-TL) from conventional CPM formula and show that the discrete spectral lines appeared in the power density spectrum of CPM-TL signals can be diminished or become negligible by appropriately choosing PSP. We also show that this class of CPM can use any real number modulation index (h) and the resultant trellis structure of CPM guarantees the maximum constraint length allowed by the number of states in the MLSD receiver. Finally, the energy-bandwidth performance of CPM using time-limited PSP is investigated and compared with conventional CPM with time-unlimited PSP. From numerical results we show that, under the same number of states in the MLSD receiver and bandwidth occupancy, this subclass of CPM could outperform the conventional CPM up to 6dB coding gain, for h<1, in many cases.

We present transmission- and reflection-type measurement methods for the differential mode delay (DMD) of a multimode optical fiber (MMF) optimized for high-speed local area networks (LANs) for the 850-nm band. Compared with a previously reported transmission-type measurement method for the 1550-nm wavelength band, we demonstrate here high-resolution DMD measurement methods for MMFs in the 850-nm band. As the method is based on a Fourier-domain intermodal interference technique, the measurement sensitivity is ∼60-dB, and it requires a fiber only a few meters in length. The shorter wavelength also allows a threefold improvement in the measurement resolution. The reflection-type measurement technique is a more practical than the transmission-type measurement technique for the field testing of short MMFs already installed in networks. We believe that this method will be a practical tool not only for field testing of short-length MMFs already installed in networks but also for the development of new plastic optical fibers (POFs).

Recently, many kinds of content are being circulated within a great many service-specific overlay networks. When the content is not extremely delay-sensitive, content circulation between wireless terminals can be realized without additional resources by using off-peak periods in wireless access links. In such content circulation, peer-to-peer content multicast is a promising approach to reduce the load on the centralized server. However, to minimize battery drain, each wireless terminal can only forward content to a restricted number of neighboring terminals once it has received the content. This paper proposes an efficient forwarding scheme for peer-to-peer content multicast between the wireless terminals intermittently connected with the backhaul network. In the proposed scheme, a restricted number of terminals with an earlier start time of off-peak periods are selected to forward the content when the number of forwarding hops from the source terminal is less than or equal to a predetermined threshold. In contrast, a restricted number of terminals are selected randomly when the number of forwarding hops exceeds the threshold. This paper clarifies that the proposed hybrid forwarding scheme can multicast the content to many terminals within an arbitrarily restricted period. A guideline to determine the optimum threshold for switching the terminal selection method in the proposed hybrid scheme is derived from simulation results.

Due to vehicle movement and lossy wireless channels, providing a reliable and efficient multi-hop broadcast service in vehicular ad hoc networks (VANETs) is a well-known challenging problem. In this paper, we propose BR-NB (broadcast with neighbor information), a fuzzy logic based multi-hop broadcast protocol for VANETs. BR-NB achieves a low overhead by using only a subset of neighbor nodes to relay data packets. For the relay node selection, BR-NB jointly considers multiple metrics of the inter-vehicle distance, vehicle mobility and link quality by employing fuzzy logic. Since the expected coverage and vehicle mobility are inferred from the two-hop neighbor information which can be acquired from the hello message exchange, BR-NB is independent of position information. BR-NB provides a practical and portable solution for broadcast services in VANETs. We use computer simulations and real-world experiments to evaluate the performance of BR-NB.

For real-time video streaming, tree-based Application Level Multicasts (ALMs) are effective with respect to transmission delay and jitter. In particular, multiple-tree ALMs can alleviate the inefficient use of upload bandwidth among the nodes. However, most conventional multiple-tree ALMs are constructed using a Distributed Hash Table (DHT). This causes considerable delay and consumes substantial network resources because the DHT, generally, does not take distances in the IP network into account. In addition, the network constructed by a DHT has poor churn resilience because the network needs to reconstruct all the substreams of the tree network. In this paper, we propose a construction method involving overlapped cluster trees for delivering streamed data that are churn resilient. In addition, these overlapped cluster trees can decrease both the delay and the consumption of network resources because the node-connecting process takes IP network distances into account. In the proposed method, clusters are divided or merged using their numbers of members to optimize cluster size. We evaluated the performance of the proposed method via extensive computer simulations. The results show that the proposed method is more effective than conventional multiple-tree ALMs.

Tunneling is one of the main methods for the transition from IPv4 to IPv6 networks. By encapsulating IPv6 packets in IPv4 or UDP packets, tunnels like 6to4, Isatap and Teredo provide a feasible way for IPv4 hosts to establish IPv6 connections to hosts in IPv6 internet or IPv6 islands. For IPv4 internet, the use of tunnels varies the traffic and increases the type of packets, making the network environment more complex. In addition to common tunnels, various types of tunnels with more layers are tested in this paper. The results of successful connections prove the usefulness of multi-layer packets with diverse layer-count and type on the internet. To ensure the security of internal networks, the influence on traffic analysis in dual-stack IDS devices caused by the diversity is studied. Three spoofing attacks of “data insertion”, “data evasion” and “attacks using UDP” are proposed to show the influence on IDS caused by tunnels. Compared to the attacks without tunnels, some constraining factors are eliminated, which may increase the security risk of IDS and decrease the attacker's difficulties. To summarize this kind of problem, the concept of “Tunnel Interference” is revealed. And as solutions to this problem, two methods, RA (Record All) and HEH (Hash for Each Header), are presented in this paper which theoretically solve these problems to a great extent. RA records all headers and compares from the outermost to innermost layer. HEH is hash-based and accumulates hash values of each header. Both of them have linear time and space complexity. Experimental results show that RA and HEH will lead to minor space increase and up to 1.2% time increment in each layer compared to the original dual-stack.

This paper describes a novel technique to replace some of the driven elements in an array antenna with parasitic elements. First, the antenna characteristics are studied by simulation for a basic unit array with one driven and two parasitic elements. The entire antenna is backed with a flat reflector to conform to practical applications. The parasitic elements are excited by the neighboring driven elements through the electromagnetic coupling effect. It is shown that at the optimal coupling condition, the radiation patterns are almost identical with those of an array antenna whose elements are all driven without coupling. The simulation result is confirmed by performing an experiment at 5.8GHz (λ =51.7mm). Finally, a 12-element array is formed by combining four unit arrays. The simulation results show that the maximum antenna gain is 19.4dBi, indicating that there is no penalty with respect to the antenna gain of a fully driven 12-element array. Therefore, the array antenna can be considerably simplified by replacing 67% of its elements with parasitic elements.

Light weight RLSAs with a honeycomb-type parallel plate are promising candidates for satellite antennas. However, the design of slot lengths and positions in honeycomb RLSAs consisting of a core, skin and adhesive layers involves time-consuming EM analysis. In this paper, an equivalent double layer model is devised for fast slot coupling analysis by the Method of moments (MoM) together with a simplified array design procedure. A fabricated antenna with a diameter of 900mm demonstrates the high directivity of 48.3dBi and a gain of 44.6dBi at 32GHz, with the reflection below -15dB. This antenna weighs only 1.16kg.

In this paper, a practical antenna selection (AS) scheme is investigated for downlink multiuser massive multiple input multiple output (MIMO) networks where a base station (BS) is equipped with many antennas (N) and communicates with K mobile stations (MSs) simultaneously. In the proposed antenna selection technique, S antennas (S≤N) are selected for transmission based on the knowledge of channel coefficients of each MS for reducing the number of RF chains which mainly induce cost increase in terms of size, hardware, and power. In the proposed AS technique, a BS first ranks antenna elements according to the sum of their channel gains to all MSs. Then, the BS computes the downlink sum-rate with S consecutive antenna elements in the ordered set, where the subset consisting of S consecutive antennas is called a window. The BS selects the window resulting in the highest sum-rate. The selected S antenna elements are used for transmitting signals to multiple users, while the remaining (N-S) antenna elements are turned off for the time slot. Therefore, the proposed AS technique requires only (N-S+1) sum-rate computations, while the optimal AS technique involves $inom{N}{S}$ computations. We analyze downlink sum-rate with the proposed AS technique and compare it with that of a reference system with the same number of antenna elements without AS. Our results show that the proposed AS technique significantly outperforms the reference scheme.

In this study, we investigate the use of scheduling algorithms to support coordinated multipoint (CoMP) operation for Long Term Evolution (LTE)-Advanced systems studied in the 3rd Generation Partnership Project (3GPP). CoMP, which improves cooperative transmission among network nodes (transmission points: TPs) and reduces or eliminates interTP interference, enabling performance improvements in cell edge throughputs. Although scheduling algorithms in LTE systems have been extensively investigated from the single cell operation perspective, those extension to CoMP where each user equipment (UE) has multiple channel state information (CSI) feedbacks require further consideration on proportional fairness (PF) metric calculation while maintaining PF criteria. To this end, we propose to apply a scaling factor in accordance with the number of CSI feedbacks demanded for the UE. To evaluate the benefits of this scaling factor, multicell system-level simulations that take account of channel estimation errors are performed, and the results confirmed that our improved algorithm enables fairness to be maintained.

In this paper, we introduce a new multi-operator pico eNodeB (eNB) concept for cellular networks. It is expected that mobile data offloading will be performed effectively after installing the pico eNBs in cellular networks, owing to the rapid increase in mobile traffic. However, when several different operators independently install the pico eNBs, high costs and large amounts of space will be required for the installation. In addition, when several different operators accommodate their own user equipments (UEs) in the pico eNBs, not enough UEs can be accommodated. This is because the UEs are not evenly distributed in the coverage area of the pico eNBs. In this paper, the accommodation of the UEs of different operators in co-sited pico eNB is discussed as one of the solutions to these problems. For the accommodation of the UEs of different operators, wireless resources should be allocated to them. However, when each operator independently controls his wireless resources, the operator is not provided with an incentive to accommodate the UEs of the other operators in his pico eNBs. For this reason, an appropriate rule for appropriate allocation of the wireless resources to the UEs of different operators should be established. In this paper, by using the concepts of game theory and mechanism design, a resource allocation rule where each operator is provided with an incentive to allocate the wireless resources to the UEs of different operators is proposed. With the proposed rule, each operator is not required to disclose the control information like link quality and the number of UEs to the other operators. Furthermore, the results of a throughput performance evaluation confirm that the proposed scheme improves the total throughput as compared with individual resource allocation.

This paper addresses the sensing-throughput tradeoff problem by using cluster-based cooperative spectrum sensing (CSS) schemes in two-layer hierarchical cognitive radio networks (CRNs) with soft data fusion. The problem is formulated as a combinatorial optimization problem involving both discrete and continuous variables. To simplify the solution, a reasonable weight fusion rule (WFR) is first optimized. Thus, the problem devolves into a constrained discrete optimization problem. In order to efficiently and effectively resolve this problem, a lexicographical approach is presented that solving two optimal subproblems consecutively. Moreover, for the first optimal subproblem, a closed-form solution is deduced, and an optimal clustering scheme (CS) is also presented for the second optimal subproblem. Numerical results show that the proposed approach achieves a satisfying performance and low complexity.

A deeply-coupled system can feed the INS information into a GNSS receiver, and the signal tracking precision can be improved under dynamic conditions by reducing tracking loop bandwidth without losing tracking reliability. In contrast to the vector-based deep integration, the scalar-based GNSS/INS deep integration is a relatively simple and practical architecture, in which all individual DLL and PLL are still exist. Since the implementation of a deeply-couple system needs to modify the firmware of a commercial hardware GNSS receiver, very few studies are reported on deep integration based on hardware platform, especially from academic institutions. This implementation-complexity issue has impeded the development of the deeply-coupled GNSS receivers. This paper introduces a scalar-based MEMS IMU/GNSS deeply-coupled system based on an integrated embedded hardware platform for real-time implementation. The design of the deeply-coupled technologies is described including the system architecture, the model of the inertial-aided tracking loop, and the relevant tracking errors analysis. The implementation issues, which include platform structure, real-time optimization, and generation of aiding information, are discussed as well. The performance of the inertial aided tracking loop and the final navigation solution of the developed deeply-coupled system are tested through the dynamic road test scenarios created by a hardware GNSS/INS simulator with GPS L1 C/A signals and low-level MEMS IMU analog signals outputs. The dynamic tests show that the inertial-aided PLL enables a much narrow tracking loop bandwidth (e.g. 3Hz) under dynamic scenarios; while the non-aided loop would lose lock with such narrow loop bandwidth once maneuvering commences. The dynamic zero-baseline tests show that the Doppler observation errors can be reduced by more than 50% with inertial aided tracking loop. The corresponding navigation results also show that the deep integration improved the velocity precision significantly.