Asynchronous Pulse Code Multiple Access (APCMA) has been proposed as a pulse-based LPWA technology for massive IoT, offering robustness against collisions. However, in ultra-dense environments, pulse overlaps cause misdetections. This paper proposes an enhanced CSS-APCMA decoding method that leverages per-message chirp frequency-offset consistency and accounts for clock jitter. The receiver was implemented using a USRP and GNU Radio, and large-scale experiments were conducted with 1,000 transmitters operating in the 920 MHz band. The results demonstrate that the proposed method maintains a high reception rate while significantly suppressing misdetections and achieving higher data rates compared to conventional CSS-APCMA in ultra-dense environments.

Accurately forecasting heavy rainfall disasters requires collecting wide-area maritime weather data obtained by ocean buoys without communication interruption. A low-cost approach to collect these data is a maritime sensor network using altitude-controllable light balloons with only a limited number of altitude controls. This paper analyzes the impact of the altitude controls on the spatial coverage of buoys that establish communication links with balloons within an allowable interruption duration in this maritime sensor network. To this end, this paper formulates a buoy coverage maximization problem with wind-dependent trajectories of altitude-controllable light balloons based on altitude controls and solves this problem. Our simulation results highlighted that the optimally altitudecontrolled balloons communicated with 67% of the buoys without an interruption duration exceeding one hour. Our results also showed that optimally altitude-controlled balloons achieved a 264% larger number of buoys within the allowable interruption than free-floating balloons.

This paper proposes a novel proactive deployment framework for multiple aerial base stations (ABSs) to enhance the resilience of cellular networks against post-disaster disruptions. Unlike conventional approaches that optimize the ABS deployment separately for pre and post-disaster conditions, our proposed framework jointly optimizes the ABS deployment providing high-quality services continuously from predisaster to post-disaster environments. By formulating the joint optimization problem, our strategy maximizes the minimum user satisfaction before disasters and the user coverage after disasters. Our simulation results demonstrated that our strategy significantly outperformed the existing strategies by achieving the pre and post-disaster network performance while requiring only a marginal increase in the number of ABSs.

In this paper, we investigate the influence of pulse density and misdetection of the asynchronous pulse code multiple access (APCMA) to reservoir computing in a wireless spiking neural network (WSNN). In a WSNN, sets of neurons are connected with each other by wireless communication. Therefore, the computational capability of a WSNN depends on the performance of wireless communication. APMCA accomplishes immediate and reliable wireless communication by encoding information as intervals of successive pulses, but it suffers from misdetection of messages especially when the pulse density is high. By using NARMA2 as a benchmark task, we showed that the synchronicity between modules was more important than the decrease in the pulse density to achieve the higher performance.

This paper maximizes the throughput in the grant-free power-domain non-orthogonal multiple access (GF-NOMA) for users distributed in a 3D space by optimizing the power level selection strategy. To maximize the throughput, we propose a stochastic geometry-based analytical model for an offered load per level (called per-level offered load), deciding the throughput, for 3D distributed users. The key idea is to reflect line-of-sight conditions depending on the altitudes of such users to power level constraints. This key idea enables our model to stochastically limit selectable power levels along with LoS conditions and derive a selection strategy suitable for offloading an inhomogeneous per-level offered load caused by LoS conditions to maximize the throughput. Our optimization results showed that the derived power level selection strategy achieved 16% higher throughput than the baseline strategy, where each user randomly selects a power level under the power level constraints.

This paper proposes a scalable framework to analyze the throughput of the grant-free power-domain nonorthogonal multiple access (GF-NOMA) and presents the achievable performance in the optimized offered load at each power level (called per-level offered load) by using our framework. Our analytical model reflects packet errors caused by power collisions, characterized by GF-NOMA, based on the power level design guaranteeing the required signal-to-interference-and-noise ratio (SINR). This key idea enables analyzing the throughput of a large-scale GF-NOMA system more accurately than the existing analytical models. Also, this key idea enables optimizing the per-level offered load rather than a uniform one in typical optimization problems related to the throughput: the throughput maximization or energy minimization problem with a throughput condition. Our analytical results highlight some key insights into designing future access control methods in GF-NOMA. First, our analytical model achieves an approximation error of only 0.4% for the exact throughput obtained by the exhaustive search at five power levels; the existing analytical model provides an approximation error of 25%. Next, our proposed framework highlights that the optimal per-level offered load restrictively improves the throughput above the optimally uniform per-level offered load. Finally, our proposed framework discovers a 27 more energy-efficient per-level offered load than the existing framework at five power levels while providing higher throughput than the optimally uniform per-level offered load.

This article proposes a stochastic geometry-based analytical framework for the throughput of the grant-free power-domain nonorthogonal multiple access (GF-NOMA) with user-specific constraints of selectable power levels and analyzes the achievable throughput. Our analytical framework uses stochastic geometry to reflect selectable power levels constrained by the maximum transmission power and channel of each user to an inhomogeneous offered load per level. This key idea enables our framework to analyze the throughput bounded by the geographical user distribution and derive a suitable selection strategy of power levels under the constraint more accurately than the existing models. Our analytical results showed that our framework analyzed the throughput with only an analysis error of 0.1% compared with the Monte Carlo simulations, although the existing model overestimated 58% higher throughput. By using the proposed analytical model, our results presented decreasing the achievable throughput with increasing the coverage range. This article also proposes a heuristic method based on our proposed analytical model to derive a suitable selection strategy of power levels. Our results highlight that the derived selection strategy on our analytical framework achieved 20% higher throughput than the baseline strategy, where each user randomly selects a power level under the power-level constraint.

This paper proposes a retransmission or 2-shot method using the cross-slot SIC for the grant-free power-domain non-orthogonal multiple access (GF-NOMA) in the massive machine-type communications (mMTC). The proposed method allows only the users experiencing power collisions to retransmit their packets in a quasi-coordinated fashion by order of IDs of pilot sequences. Our second-shot mechanism enhances the impacts of cross-slot SIC to recover packet errors in the first transmission due to power collisions. Our simulation results highlight that the proposed method provides 32% higher throughput than the baseline method retransmitting all the error packets.

This paper analyzes the packet reception ratio (PRR) of direct communications between unmanned aerial vehicles (UAVs), i.e., UAV-to-UAV (U2U), by using stochastic geometry tools, focusing on UAV heights. In U2U, a receiving UAV (called a UAV-Rx) experiences better line-of-sight (LoS) conditions of its communication and interference links with other UAVs distributed in a three-dimensional space at its higher height. The balance of LoS conditions of these links decides the PRR of U2U. To analyze the characteristics, we derived a closed-form expression of the PRR of U2U. Our analysis highlighted that the PRR of U2U decreased and then increased as the height of a UAV-Rx increased at the distance of the communication link of 100 m in the dense urban model, and the UAV-Rx experienced the bottom PRR at its height of 32.5 m, depending on the building heights.

The shepherding problem refers to guiding a group of agents (called sheep) to a specific destination using an external agent with repulsive forces (called shepherd). Although various movement algorithms for the shepherd have been explored in the literature, there is a scarcity of methodologies for selective guidance, which is a key technology for precise swarm control. Therefore, this study investigates the problem of guiding a single target sheep within a swarm to a given destination using a shepherd. We first present our model of the dynamics of sheep agents and the interaction between sheep and shepherd agents. The model is shown to be well-defined with no collision if the interaction magnitude between sheep and shepherd is reasonably limited. Based on the analysis with Lyapunov stability principles, we design a shepherd control law to guide the target sheep to the origin while avoiding collisions among sheep agents. Experimental results demonstrate the effectiveness of the proposed method in guiding the target sheep in both small and large scale swarms.

This paper presents the optimal position of an aerial base station (ABS) by unmanned aerial vehicle (UAV) in a heterogeneous cellular network (HetNet) at heterogeneous user traffic demands to maximize the throughput. The key idea is to consider the upper limit of the achievable throughput based on the traffic demand of each user to optimize the ABS position, optimally selecting its direct communication path to the terrestrial base station or its forwarding path via the ABS. We derive the throughput maximization problem with traffic demands and then solve this problem for the ABS position with the optimal communication paths. Our simulation results highlighted that the proposed method achieved 23% higher throughput than an existing method at heterogeneous user traffic demands.

This paper analyzes the spatial performance of the autonomous sidelink cellular-vehicle-to-everything (called ASC-V2X) with the sensing-based semi-persistent scheduling (SB-SPS) with the power-domain non-orthogonal multiple access (NOMA), called SPS-NOMA. In SPS-NOMA, multiple users (e.g., cars or pedestrians) simultaneously broadcast their packets, i.e., a packet collision, and each receiver (i.e., each of their surrounding users) aims to decode the packets by using the successive interference cancellation (SIC). However, some re-ceivers may undergo collision errors at collisions even in SPS-NOMA due to spatial location relationships between the receivers and simultaneously transmitting users, called collision users. To reveal such spatial performance characteristics, this paper derives closed-form expressions of the packet reception ratio (PRR) at the receiver deployed on each coordinate point in a spatial area. Our analysis showed the spatial distributions of the PRR in an area, and SPS-NOMA achieved the required PRR in a 50% more wide area than the existing ASC-V2X without SIC. Additionally, our analysis provided the limitations of SPS-NOMA, and specifically, receivers experienced 65 % lower PRRs than the peak around the bisector created by collision users.

This paper proposes an analytical model for the throughput of the grant-free power-domain non-orthogonal multiple access (called GF-NOMA) in the massive machine-type communications, reflecting the characteristics of packet errors. GF-NOMA designs power resources (called power levels) for each terminal to autonomously satisfy the decoding condition in NOMA. This design causes packet errors at higher-power levels than the level used by multiple terminals due to the non-orthogonality. Our proposed analytical model reflects the packet errors due to this power level design to analyze the throughput more accurately than related works. Our analytical results highlighted that our proposed model underestimated the throughput by only 0.3% over the Monte Carlo simulation at fifteen power levels. In contrast, an existing model overestimated the throughput by 68% over the simulation. Our analysis also showed the throughput characteristics and revealed that using the lowest-power level provided 89% lower throughput than using the highest-power level at ten power levels.

This paper proposes a retransmission strategy using the non-orthogonal multiple access (NOMA) in the PC5-based cellular-V2X mode 4 (called mode 4) to mitigate the channel congestion. The proposed strategy has two key ideas. The first idea is to allow each node (e.g., a car or a pedestrian) to retransmit its packet at lower transmission power than its original packet in the first transmission. The second idea is that each node aims to synchronize its low-powered retransmission with the first transmission of its neighbor node. The two key ideas boost the PRR through diversity effects by mitigating interference and providing power differences with widely deployed receivers. Our simulations highlighted that the proposed strategy outperformed the existing NOMA with retransmissions in mode 4 by 29%.

Industrial monitoring systems are developed and deployed to continuously and remotely monitor the status of industrial equipment and detect failures. A gateway node collects status data from sensors attached to machines and then sends them to a server for analysis and evaluation. In this paper, we propose a method to detect anomalies in communication between a gateway and a server over an LTE network, whose failure would bring a serious result such as an operation halt of the whole factory. We model a time series of dynamically and instantaneously changing response delay as sawtooth waves and detect an anomaly based on their statistical characteristics. Through evaluations using real measurements and artificial data, we verified that our method can detect both of constant increase and decrease, rapid increase, long-term increase, and slow decrease in the response delay.

For the realization of an Internet of Things (IoT) with high densities of nodes it is necessary that wireless communication protocols are developed that offer (1) low energy consumption, (2) simplicity of encoding and decoding, (3) an asynchronous mode of communication, and (4) an effective but simple method to deal with interference between transmissions. This paper presents the implementation, experimentation, and analysis of a protocol on the MAC sublayer that is based on the encoding of information by the silent intervals between pulses. This encoding allows for few conflicts between messages that are broadcast on the same band overlapped in time. This is demonstrated experimentally, while no adverse effect is detected on transmissions from broadcasts of a different group of nodes using the same 315 MHz band but with a different code length as coding parameter. Theoretical analysis confirms that the probability of conflicts between messages is low, even if the number of nodes increases to the order of ten thousand. This protocol facilitates the implementation of IoT nodes that are restricted in terms of hardware and energy resources.

Impulse-radio wireless sensor network is a recently proposed concept of wireless sensor network aiming to sense an extended area with high spatial resolution. Extremely simple architecture of the network enables one to install huge number of sensors to the target area. Users of the network are able to precisely estimate location of event-detecting sensor nodes by measuring time of arrivals of impulse signals at anchor nodes. The localization protocol, however, assumes that sensor nodes keep their radio receiver on all the time, which is the main obstacle to reduce energy consumption of the network. To solve the problem, here, we propose a sleep/wake-up protocol of sensor nodes for the network. We show that the protocol can reduces activity of radio receiver of each node by more than 90 % with keeping precision of localization remain intact. We numerically confirm validity of the proposed sleep/wake-up protocol for various conditions including target area with various shape.

Industrial wireless sensor network (IWSN) applications are required to provide precise measurement functions as feedback for controlling devices. Current industrial wireless communication protocols, such as ISA100.11a and wirelessHART, have difficulty, however, in guaranteeing latency for unpredictable on-demand communications. In this paper, a priority-based dynamic multichannel transmission scheme is proposed for IWSNs. In the proposed scheme, a root node controls the transmission timing of high-priority packets, while other nodes autonomously decide what channel to use and when to transmit packets to a neighbor. Simulation results show that real time control is possible where a response delay from transmission of a request to reception of a reply at a root node is within 1,140 ms at per-link communication success probability with a retry of higher than 93%.

The Internet of Nano-Things will employ wireless sensor nodes that are not only extremely small in size and large in number but also severely restricted in their power supply. While a large part of the design of such networks will rely on the engineering of physical aspects, such as developing technology for efficient energy harvesting, sensing, and communication, a significant role will also be played by the algorithms underlying the operation of nodes to ensure that optimal use is made of the limited supply of energy. This paper discusses concepts that will facilitate the design of such algorithms, such as spike-based encoding of signals and data aggregation through gossiping. We propose a method to extract information from a sensor network using nonpacket spike-based communication with local interactions between nodes. Rather than gathering sensor values from each individual node and sending them to a central destination node, measurements from the nodes are processed through the interactions between nodes, while diffusing in the network, to obtain an integrated value characteristic for all nodes' measurements.

Network virtualization technologies enable multiple virtual networks to be laid over common physical networks and provide application or service-oriented networking functionalities in each virtual network. Since virtual networks share and compete for physical network resources, cooperation between virtual networks is necessary to accomplish the system-level optimization. Furthermore, system-wide adaptation is required to react to dynamically changing traffic conditions which cannot be controlled nor predicted by each virtual network. In this paper we propose an adaptive multipath routing mechanism with which globally suboptimal control can be accomplished. For this purpose, we adopt a bio-inspired algorithm, more specifically, an attractor selection model which is a nonlinear mathematical model of biological adaptation. We consider layered network architecture where a virtual network consists of virtual nodes and links which are generated by virtualizing physical domain networks and physical links. In our proposal each of physical and virtual nodes adaptively selects one of pre-established paths in accordance with dynamically changing network conditions. For cooperative routing decisions, we introduce a mechanism for routing controls operating at different virtual networks to share optimization objectives. With such loose inter-network coupling, our proposal is superior to existing control from viewpoints of adaptability and stability.

Machine Type Communications (MTC) has been paid much attention as a new communication paradigm to increase mobile network traffic. Most of MTC terminals are time-driven, that is, they send and receive data periodically. Therefore, network access requests on mobile core networks are concentrated at a specific timing, which results in instantaneous increase in network load. Considering the fact that such time-driven MTC would accept a certain amount of latency in their cyclic communication, in this paper, we propose a scheduling method of communication timings of time-driven MTC terminals to mitigate traffic concentration. We extend the standardized back-off mechanism of 3GPP to configure the back-off time length for each terminal to decrease the number of concurrent bearers in the network, while satisfying requirements on communication latency. We compare proposed methods by simulation experiments and reveal that we can achieve almost zero access rejections at reasonable communication quality by a simple timeslot selection algorithm when the core network maintain the timeslot assignment status for accommodated User Equipments. To the best of our knowledge, this is the first proposal to alleviate short-term congestion of mobile core networks by MTC with TDMA-like network control.

A new generation network is expected to keep operating and providing users and applications with means of communication while being exposed to dynamic and substantial change in the operational environment such as network topology, traffic, and QoS requirement. To establish a highly adaptive and reliable network, we take an approach to be inspired by biological systems, which adapt themselves to dynamically changing and even unexpected environment. In this paper we show examples of application of bio-inspired models, more specifically the attractor selection/composition models built on adaptive behavior of biological systems, to autonomous and adaptive networking in wireless communication systems. The first application is MANET routing, where a path connecting a source-destination pair must be maintained under dynamically changing environment. The second application is resource allocation among nodes and applications competing for wireless networks with heterogeneous characteristics. We further discuss future direction of bio-inspired adaptive networking.

In this paper we propose a clustering and data gathering scheme for wireless sensor networks, based on a biologically-inspired approach that uses the concept of adaptive response by attractor selection as observed in a gene network. The approach uses a layered concept of clustering and routing that work independently, yet, resulting in an interdependent interaction via a common activity factor. This approach is aimed at establishing resilience and robustness in a two-layered protocol, where the network would perform a distributed clustering and routing of data to a sink. In this scheme, cluster heads are chosen according to their relative residual energy and routing is performed upon the relative cached data sizes and energy recharging rates of the next hop gateway nodes.

This paper introduces a new sensor network testbed, X-sensor, that integrates multiple sensor networks deployed at different sites. X-sensor provides three functionalities: (a) a sensor network search which enables users to find a sensor networks appropriate for experiment and data acquisition, (b) a sensor data archive which provides users with various sensor data acquired by sensor nodes, and (c) an experimental testbed which enables remote users to evaluate their network and data management protocols.

In this paper we propose a transmission range reduction scheme for a clustered wireless sensor network (WSN), in order to reduce power consumption while maintaining the network connectivity, particularly in scenarios where consecutive reporting of sensing values is inherent in the network. The platform WSN is based on a multi-hop clustering algorithm, where clusterheads send information to the sink via either gateway nodes or other clusterheads of intermediate clusters towards the sink. The main idea of this scheme is that the sink initially gathers the number of nodes or clusters in the network and instructs the reduction in the transmission range of the sensors until this number, hence connectivity is compromised. The proposed scheme does not require geographical information of nodes, and is independent of propagation model and environmental conditions that may cause non-uniform attenuation to radio signals. Furthermore, the scheme is independent of network topology, and can be applied to both uniform and non-uniform distribution of nodes. Simulation results show the effectiveness of the approach in two different clustering schemes, in regards to reducing energy consumption in the network.

Abstract In this paper we propose an energy‐efficient self‐organizing global extremity reporting scheme for wireless sensor networks. The proposed scheme assists applications of periodic reporting of extreme values (such as maximum or minimum temperature/pressure) across a wireless sensor field, back to the sink. Furthermore, an event‐driven counterpart is supplied for individual sensor nodes to supply their instantaneous sensed values back to the sink, once queried. The targeted sensors initially establish their relative distances to the sink in regards to number of hops, whilst the highest hopcount nodes (HHNs) from the sink identify themselves. The broadcast initiation of the HHNs have the ability to penetrate all nodes within the network towards the sink, and hence obtain the extreme value of the entire network in an efficient manner. This is due to the relative position of these special nodes within the network. Furthermore, the scheme does not require nodes to possess location information of themselves or other nodes, avoiding the need for the global positioning system (GPS) or other location‐aware methods. Simulation results show the effectiveness of the proposed protocol in its target application. In particular, the advantage of HHN‐initiated broadcasting can be seen in both uniformly and randomly distributed topology networks. Copyright © 2008 John Wiley & Sons, Ltd.

In this paper we propose an architecture which integrates the notion of self-adaptability and self-organization in the pervasive computing architecture. Furthermore we describe how a biologically-inspired approach may be a good candidate for this purpose in order to provide a resilient, self-adaptive system similar to living biological systems. Additionally the emergent intelligence that would ultimately encompass the human being and its environment would inevitably assist us where our consciousness is not present.

In ambient information society, a variety of networks consisting of sensory and computational devices are embedded in the environment and individuals. They are autonomously connected, merged, and divided depending on the context and provide a network service appropriate for time, place, occasion, and individuals. In this paper, we investigate how such dynamic network formation is performed focusing on synchronization of operational frequency. Assuming that a pulse-coupled oscillator model is adopted for autonomous and self-organizing synchronization, we show how networks operating on different operational frequency are connected, merged, and divided.

In this paper, we discuss robustness issues of a biologically inspired routing protocol for mobile ad hoc networks and the influence it has on the quality of service (QoS) in the system. Contrary to fixed network structures, ad hoc networks are susceptible to frequent topology changes due to the mobility and churn of the participating nodes. Our goal is therefore to provide fast recovery from connectivity failures, as well as a fast reaction to path changes due to node mobility or churn.

The wireless sensor network (WSN) is one of the most promising technologies which helps making our society safe, secure, and comfortable. A WSN as a social infrastructure must transmit critical information faster and more reliable than other information. In this paper, we propose an autonomous and distributed mechanism, called an "assured corridor" mechanism (ACM), for fast and reliable transmission for urgent information in WSNs. In ACM, a self-organizing corridor consists of nodes surrounding the path from the source node to the base station and nodes in the path. The former refrains from transmitting non-urgent information to avoid collisions with emergency packets, and the latter suspends their sleep schedule and keeps awake to avoid delay caused by sleeping. We conducted simulation experiments with a tree-based and broadcast-based network. It was shown that ACM improved the delivery ratio and the delay of emergency packets.

In this paper, we propose a self-organizing communication mechanism for a wireless sensor network where a large number of sensor nodes are deployed. To accomplish application-oriented periodic communication without any centralized controls, we adopt traveling wave phenomena of a pulse-coupled oscillator model by regarding sensor nodes as oscillators and the emission of radio signals as firing. We first investigat conditions of a phase-response curve to attain wave-formed firing patterns regardless of the initial phase of oscillators. We adopte the derived phase-response curve to accomplish the desired form of message propagation through local and mutual interactions among neighboring sensor nodes. Through simulation experiments, we confirm that our mechanism can gather or diffuse information effectively in accordance with the application's requirements.

In a P2P file-sharing system, a node finds and retrieves its desired file. If multiple nodes cache the same file to provide others, we can achieve a file-sharing system with low latency and high file availability. However, a node has to spend costs, e.g., processing load or storage capacity, on caching of a file. Consequently, a node may selfishly behave and hesitate to cache a file. In such a case, there is a possibility that unpopular files disappear from the system. In this paper, we aim to accomplish effective caching in the whole system that emerges from autonomous and selfish node behavior. We first discuss relationship between selfish node behavior and system dynamics according to evolutionary game theory. As a result, we show that a file-sharing system can be robust to file disappearance depending on a cost and demand model for caching even if nodes behave selfishly.

Wireless sensor networks used as a social infrastructure must be capable of differentiating and prioritizing transmission of urgent sensor information over other non-urgent information. In this paper, we developed a novel and simple network architecture, in which sensor information is classified into three traffic classes and each node activates one or more of several simple, self-organizing, and fully-distributed mechanisms in accordance with the scale of an emergency for fast and reliable transmission of urgent sensor information. In the demonstration, we show the operation of preferential transmission of urgent information under this architecture in a wireless sensor network.

We have proposed a simple and energy-efficient communication mechanism which can organize a variety of communication depending on dynamically changing application requirements. In this demonstration, we show that our mechanism can gather or diffuse information in accordance with application requirements in a dynamic wireless sensor network.

Providing end-to-end reliability for data transmission is a major challenge for energy-constrained and bandwidth-limited wireless sensor networks. To meet this challenge, attempts have been made using a multi-path transmission mechanism that encodes an information bitstream using forward error correction (FEC), and sends the obtained packets over a number of paths to the destination. Algorithms that, given the paths statistics (e.g., failure probability and energy cost of data transmission over the paths), find the number of channel packets and their transmission paths that optimize the reliability-energy cost tradeoff have been proposed. Once a transmission strategy is obtained, all packets are transmitted regardless of the actual state of the wireless links, which may result in energy and bandwidth losses due to unnecessary transmissions. This can be more severe when arbitrary transmission strategies have to be used due, for example, to the unavailability of paths statistics at the source node, which is the case in many practical applications. In this paper, we propose a hybrid FEC-feedback mechanism. The feedback scheme is used to send ACK packets from the sink to the source node when the information bitstream is actually recovered. We then derive a measure of the expected energy cost of data transmission for the hybrid mechanism. Simulation results show that, on average, the hybrid mechanism consumes up to about 44% less energy than the FEC-based mechanism for the transmission of a bitstream with the same reliability constraint. The energy savings of the hybrid mechanism are even higher when arbitrary transmission strategies have to be used.

Taking into account requirements of sensor networks, we need fully-distributed and self-organizing control mechanisms which are scalable to the size of a network, robust to failures of sensor nodes, and adaptive to different and dynamically changing topology and changes in wireless communication environment. To accomplish this goal, our research group focuses on behavior of biological systems, which inherently are scalable, adaptive, and robust. In this paper, we first verify the practicality of control mechanisms adopting a reaction diffusion equation, which explains emergence of patterns on the surface of body of fishes and mammals, and then propose two methods for faster pattern generation to save energy consumption. From simulation and practical experiments on a prototype, it was shown that a stable pattern could be generated in a wireless sensor network in several minutes, even when packets were lost for collisions in wireless communication.

In this paper, we propose and evaluate a self-organizing communication mechanism for wireless sensor networks where a large number of sensor nodes are deployed. To accomplish application-oriented periodic communication without any centralized controls, we adopt traveling wave phenomena of a pulse-coupled oscillator model by regarding sensor nodes as oscillators and emission of radio signals as firing. Through simulation experiments, we confirm that our mechanism delivers sensor information to / from a designated node in a more energy-efficient manner than other method, although it takes time to generate a traveling wave. In addition, we implement our mechanism using MOTE MICAz and verify its practicality.

In wireless sensor networks, the power of energy- constrained sensor nodes is largely drained by data communication tasks. Designing energy-efficient data communication mechanisms is, therefore, a major key to maximizing the life-time of wireless sensor networks. This challenge is magnified for visual sensor networks, where the collected and transmitted data is often very large and composed of multiple signals (Infrared signals, audio, video, ...) which have different and varying quality of service requirements (QoS). Motivated by this challenge, we investigate a forward error correction recovery mechanism for multi-path data transmission in wireless sensor networks. Based on this mechanism, we propose a fast algorithm for the trade-off between the end-to-end energy cost and reliability requirement of multi-path data transmission. Under the practical considerations of a fixed transmission power and a realistic modulation scheme, we derive the reliability and expected energy cost metrics of transmission paths. We then demonstrate the efficiency of our algorithm through simulations and discuss future work.

Since a peer searches for its desired file in a P2P file sharing system, the structure of an overlay network determines the effectiveness of search. In this paper, based on the Barabasi-Albert (BA) model, we propose a novel scheme (LLR) to construct a low-diameter and location-aware overlay network where peers can easily find physically-close file holders. LLR has a rewiring method to improve the structure of an overlay network and a recovery method to cope with disappearance of peers. Through several simulation experiments using real physical topologies, we found that LLR could construct an overlay network that had the higher reachability than BA and the higher correlation between physical and logical distances

In this paper we propose MARAS, a biologically-inspired method for routing in a mobile ad-hoc/sensor network environment. We assume that all nodes have no explicit knowledge of the network topology, except for their coordinates and the neighboring nodes within an RF transmission range. MARAS then selects the next hop for forwarding a packet towards a destination node which is best suited depending on some measured metric values. The benefit of our proposed method is its ability to operate entirely in a self-adaptive manner and that it can easily compensate for sudden changes in the topology of the network.

The paper investigates TCP-friendly video streaming over wireless channel using forward-error-correction (FEC). A FEC scheme is used as an intra-protection control based on Hamming code. Coded BPSK scheme is applied over AWGN wireless channel to be robust against frequent packet loss. For this purpose, we propose variable frame rate based on TCP-friendly rate control (VFR-TCP) model. The model estimates the predicted frame rate for MPEG video streaming. Quality of service (QoS) is also accounted for the predicted quantizer scale Q if the network throughput is assumed to be equal the available bandwidth. Simulation results show that the VFR-TCP model increases tolerance to packet loss due to channel bit errors and achieves a good quality

In this paper we discuss the effects of symbiosis when using an attractor selection model for multi-path routing in an overlay network. Attractor selection is a biologically inspired approach which is found in E. coli cells to self-adaptively react to changes of a nutrient in the environment. It is driven by noise and we present its application to selecting the paths in an overlay network for the transmission of a packet. This selection is performed with randomization to reduce the selfishness of each flow and to improve the overall performance of the network. Our main focus in this paper lies on showing the symbiotic behavior in the interaction of competing flows

One can obtain information about a region by deploying a network of sensor nodes there. Since remotely deployed nodes are usually powered by batteries, an energy-efficient data gathering scheme is needed to prolong the lifetime of the sensor network. We proposed a novel scheme for periodic data gathering but evaluated it only in simulation experiments assuming ideal environments. In this paper, we evaluated the scheme experimentally in small networks consisting of commercial, off-the-shelf wireless sensor units. We also developed mechanisms to solve problems due to the instability of radio communications and demonstrated the effectiveness of these mechanisms experimentally. We confirmed that energy-efficient data gathering can be implemented by using our proposed scheme with several improvements and that synchronization can be established and maintained under unstable and changing conditions.

Simultaneous overlay networks compete for network resources and disrupt each other. If they cooperate with each other, the collective performance can be improved and they can coexist comfortably. Taking inspiration from biology, in this paper the authors presented a model of symbiotic overlay networks. Coexisting overlay networks dynamically evolve, interact with each other, and change their internal structures. Overlay networks in a symbiotic condition eventually establish the strong relationship and finally merge into one. The effect of interconnection of two overlay networks from the viewpoint of the robustness and the rate of message dissemination was also evaluated.

With the development of low-cost microsensor equipment having the capability of wireless communications, sensor network technology has attracted the attention of many researchers and developers. By deploying a large number of sensors in a monitored region and composing a sensor network of them, one can remotely obtain information on behavior, condition, and position of elements in the region.

With the growth of computing power and the proliferation of broadband access to the Internet, media streaming has widely diffused. Although the proxy caching technique is one method to accomplish effective media streaming, it cannot adapt to the variations of user locations and diverse user demands. By using the P2P communication architecture, media streaming can be expected to smoothly react to network conditions and changes in user demands for media-streams. We propose efficient methods to achieve continuous and scalable media streaming system. In our mechanisms, a media stream is divided into blocks for efficient use of network bandwidth and storage space. We propose two scalable search methods and two algorithms to determine an optimum provider peer from search results. Through several simulation experiments, we show that the FLS method can perform continuous media play-out while reducing the amount of search traffic to 1/6 compared with full flooding.

To provide distributed multimedia applications with end-to-end QoS (quality of service) guarantees, resource reservation-based control mechanisms should be employed in both networks and end systems. In this paper, we propose a resource allocation scheme for real-time video multicasting described as a utility maximization problem. In this scheme, clients are first divided into multicast groups by means of a clustering technique. Then system resources are allocated to each group so that the total utility is maximized. We have confirmed that our proposed scheme can achieve effective use of resources while providing high-quality video to users.

As the use of real-time multimedia applications increases, the bandwidth available to TCP connections is oppressed by "greedy" UDP traffic and their performance deteriorates extremely. In order that both TCP and UDP sessions fairly co-exist in the Internet, UDP sessions should properly react against congestion as TCP. We implement a "TCP-friendly" rate control mechanism suitable to video applications and investigate its applicability to a real system through observation of the video quality at the receiver. It is shown through our experimental system that we can achieve high-quality and stable video transfer while fairly sharing the network bandwidth with TCP by applying our rate control at a control interval of 16 or 32 times as long as the round trip time (RTT).

The rate control method of MPEG-2 over the ATM DBR service class is proposed. It is intended to guarantee the quality of service required by video applications. The disadvantages of MPEG-2 Test Model 5 are resolved by introducing the bandwidth re-negotiation with the network. And user-oriented high quality video transfer can be guaranteed with the method.

An ATM switch with both input and output buffers provided with a back-pressure function has been proposed as a cost-effective switch architecture. The back-pressure function prohibits cell transmission from the input buffer to the corresponding output buffer to avoid cell loss at the output buffer due to a temporary congestion. Especially when this switch is applied to ATM LANs for data transfer services, its performance should be evaluated by taking into account bursty traffic. In this paper, we show the maximum throughput, the packet delay distribution, and the approximate packet loss probability of such an ATM switch for bursty traffic through an analytic method. In addition to a balanced traffic condition, an unbalanced traffic and a mixture of bursty and stream traffic are also analyzed. Through several numerical examples, we quantitatively show the effects of the average packet length and the output buffer size on its performance. Key words: ATM LAN, Input/Output Buffered Type S...