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In the future, wireless sensor networks (WSNs) are expected to play an important part in our everyday life. Sensor nodes are becoming more and more miniaturized, equipped with radio transceivers, and deployed in large quantities. However, due to their limitations in computational and communication capabilities, clustering techniques are usually applied for energy conservation, where designated nodes known as cluster heads collect data from their nearby cluster members and route the data in a multi-hop manner towards a the required final destination, known as a sink. However, as the number and heterogeneity of nodes increases, a distributed control becomes a necessary requirement. In this paper, we discuss the dynamics in the interactions among a multi-layered self-adaptive clustering protocol for WSNs, separated in clustering and routing layers. Each layer operates independently and utilizes a biologically-inspired adaptation scheme allowing the layers to interact and adapt to environmental changes effectively and in a self-organized manner.

For the emerging concept of network virtualization where a multitude of virtual networks (VNs) coexist, the main challenge is to isolate and control the resources allocated for individual virtual networks. Realizing such resource allocation requires deliberate design of the router enhanced specifically for handling a large number of virtual network flows. This paper discusses fundamental challenges on modeling the architecture of modern routers for the support of the virtual networks. Our intention is to discuss strategies for scheduling the traffic on each isolated VN and to provide an elementary framework for evaluating the performance of the router extended to classify incoming VN traffic. Furthermore, we also present simulation results and discuss challenges and future directions encountered in the implementation and deployment of VNs.

Using distributed hash tables (DHTs) over wireless sensor networks (WSNs) as the overlay layer has gained much attention recently because of its well designed topology and efficient data management [1]. The data of sensor nodes are stored in the overlay network, which ensures the data integrity against node failures. Nodes in a WSN are randomly deployed and may switch to sleep mode or fail due to the energy depletion, which results in changes of the network topology. Retrieving data is therefore a challenging task in such distributed and varying environments. Query latency is the most important performance metric in DHT and may not be proportional to the hop count along a route. Proximity neighbor/route selection (PNS/PRS) are used to find the shortest route and reduce latency based on the basic DHT routing. However, most existing works on PNS and PRS suffer from high overhead and frequent node arrival and departure (churn). Therefore, we propose a proximity-aware routing algorithm based on Pastry [2], dubbed PastryAS, to provide self-adaptive selection of routes and neighbors based on attractor selection [3], a biologically inspired model which operates well in ambient and fluctuating environments. Attractor selection performs a stochastic adaptation of its system state taking into account environmental changes by to an activity term, and converges to a stable state known as an attractor. In Pastry, each node has a unique ID and maintains a leafset and routing table, which corresponds to the partition of the node ID space. We propose a redundant routing table (RRT) to implement both route selection and parallel query forwarding. A passive routing table maintenance scheme is used to piggyback the routing information onto the query requests and ACKs. Only r candidates with IDs within a particular range are stored in the RRT entry as possible states, among which attractor selection is performed inspired by the equations in [3]. The performance of the selected route, such as the measured RTT, is mapped to the activity and influences the next selection. Finally, an attractor is selected from close-by neighbors. Since the topology of WSNs is always changing, whenever a node discovers new neighbors or their departure, the activity becomes low and drives the node to search for a new attractor solution. Thus, a low latency is achieved after several selections without any explicit probing and it is also maintained under churn. Parallel query forwarding is enabled by the nodes with sufficient bandwidth to achieve less timeouts and quick dissemination of the routing information. Compared with the original Pastry, we expect Pastry-AS to achieve lower latency in routing and less overhead in the routing table maintenance. In a dynamic network, RRT and parallel forwarding achieve a very low probability of timeouts, which further reduces the latency.

In this paper we discuss the application of a biologically-inspired approach for path selection in overlay networks under the constraints of in-order packet delivery. We apply the concept of attractor selection by modeling the path selection process in multipath overlay as a stochastic dynamical system that instantaneously converges to a sufficiently good solution utilizing the system inherent noise to provide a robust and adaptive mechanism. Our method is inspired by a mathematical model for the stochastic dynamics of gene regulatory networks. Simple numerical simulations will show that this proposed method is stable to changes in the environment and adaptable to the objective function, which is in our case the buffer occupancy level of the destination node in an overlay network.

In this paper we analytically derive the sojourn time of a user accessing an online IPTV recording service. Basically, the system consists of a server (or server farm) and the bandwidth at which a user can download recorded files depends on the number of other concurrently downloading users. In particular, we consider both cases, one in which the user's download speed is limited by his own access bandwidth, whereas in the other case the server is the bottleneck and all downloading users share the server's upload capacity. Our model includes user impatience which depends on the actual download speed. A user may abort his download attempt if a threshold duration is exceeded. The file size distribution is obtained by measurements of offered files at an existing server.

In this paper we propose a protocol that uses mobility information and attractor-selection to effectively and adaptively establish stable communication in mobile ad hoc networks (MANETs). The aim of this approach is to not only establish stable durable communication paths between mobile entities, but also to create a resilient network which can quickly recover from unexpected changes in the network topology. In the proposed protocol, links will have longer lifetimes and break less frequently (as a result of mobility) and the established network will be more stable and resilient to sudden changes in network topology.

Television over the Internet (IPTV) is regarded as the killer application for next generation networks (NGN). While the ITU is currently moving toward the standardized of IPTV, several existing applications like Joost and Zattoo are currently already providing a large amount of video content to Internet users. In this paper we study some popular video content delivery mechanisms and characterize them by measurements to study the user-perceived quality of experience (QoE).

In this paper we evaluate the performance of a content distribution service with respect to reliability and efficiency. The considered technology for realizing such a service can either be a traditional client/server (CS) architecture or a peer-to-peer (P2P) network. In CS, the capacity of the server is the bottleneck and has to be dimensioned in such a way that all requests can be accommodated at any time, while a P2P system does not burden a single server since the content is distributed in the network among sharing peers. However, corrupted or fake files may diminish the reliability of the P2P service due to downloading of useless contents. We compare a CS system to P2P and evaluate the downloading time, success ratio, and fairness while considering flash crowd arrivals and corrupted contents.

In structured peer-to-peer (P2P) networks participating peers can join or leave the system at arbitrary times, a process which is known as churn. Many recent studies revealed that churn is one of the main problems faced by any Distributed Hash Table (DHT). In this paper we discuss different possibilities of how to estimate the current churn rate in the system. In particular, we show how to obtain a robust estimate which is independent of the implementation details of the DHT. We also investigate the trade-offs between accuracy, overhead, and responsiveness to changes.

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.

In recent years, interesting phenomena were revealed where the inherent noise enhances the adaptability of a system to its changing environment in a resilient manner. The application of such methods can be found in a wide variety of fields, from biology to engineering. In this paper we discuss the application of noise-assisted mechanisms to control and manage information networks. Specifically, we focus on two mechanisms, stochastic resonance and adaptive response by attractor selection, and show how they can be applied in self-adaptive network control to improve the robustness and reliability of the system.

The lack of a biomarker for chronic pain remains an important impediment to clinical and translational pain research. The problem stems from the multiple parallel but subtle abnormalties thought to represent the chronic pain state, yielding the emerging view of chronic pain as a ‘network disorder’. This suggests analysis approaches that aim to identify distributed patterns of data (multivariate, machine learning methods) might offer the best opportunity to discover biomarkers. Here, we performed a multi-center functional brain imaging study to record state functional brain networks resting in 41 patients with chronic back pain and 33 healthy control subjects. We calculated with functional covariance matrix from 160 regions of interest, and used Sparse Multinomial Logistic Regression to classify subjects as patient or control using a leave-one-out cross validation. Diagnostic accuracy was 91.9%, with sensitivity and specificity 90.2% and 93.9% respectively. We then used graph theoretic measures to characterise the pattern of network differences between the groups, and showed that the chronic pain state was associated with disrupted network ‘assortativity’. These data provide evidence to support an accurate functional biomarker of chronic pain, and open the door to the development of translatable biomarkers using similar methodologies in animals.

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.

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

In this paper we propose a resilient scheme for multi-path routing using a biologically-inspired attractor selection method. The main advantage of this approach is that it is highly noise-tolerant and capable of operating in a very robust manner under changing environment conditions. We will apply an enhanced attractor selection model to multi-path routing in overlay networks and discuss some general properties of this approach based on numerical simulations. Furthermore, our proposal considers randomization in the path selection which reduces the selfishness and improves the overall network-wide performance.

The introduction of third generation mobile communication systems allows the service providers to offer a large variety of services which are in the Universal Mobile Telecommunication System subsumed under the categories conversational, streaming, interactive and background class. While the conversational and streaming classes have a guaranteed bandwidth and delay, the interactive and background class consume the remaining system capacity. On the downlink this system capacity is limited by the base station transmit power and on the uplink by the interference. In our analysis we approximate the capacity which the services with quality of service leave for best-effort services belonging to the interactive class. The background class is neglected. We focus our analysis on the downlink since for UMTS the expected traffic is assumed to be asymmetric with the bulk of it towards the mobile station and derive the distribution of the bandwidth available for best-effort users according to a spatial user distribution.

We present a method for a fast prediction of the coverage area on the uplink of a Universal Mobile Telecommunication System (UMTS) network with non-homogeneous traffic. The coverage radius of a base station depends on the interference distribution at this base station since it determines the transmit powers required from the mobile stations (MSs). The interference comprises both the own cell interference and the other cell interference which again depend on each other. Our proposed model for the computation of the interference distribution is based on an iterative solution of fixed-point equations which describe the interdependence of the interferences at neighboring base stations. Furthermore, we develop an efficient algorithm based on lognormal approximations to compute the mean and standard deviation of the other cell interference. We show that our model is accurate and fast enough to predict efficiently the coverage area which is one of the key tasks in the planning process of UMTS networks.

In cellular wideband code division multiple access (WCDMA) networks, interference on the uplink is the limiting factor for the number of users that can be served in a single cell. Thus, interference reduction mechanisms are of significant importance. Soft handover, which is primarily a mechanism for seamless handovers (make before break), also reduces the interference within the cells by exploiting multiple simultaneous connections to lower the transmit power of the mobile stations. We present an analytical model for soft handover where multiple connections between a mobile station and the base stations within reach are taken into account. An approximation of the frame error rate based on the received signal strength in the uplink is provided for 12.2 kbps service. In addition the approach taken to calculate the soft handover gain is described and results are presented.

We present an analytical model for computing the othercell interference distribution in a third generation UMTS network with inhomogeneous user distribution. Our proposed model is based on an iterative calculation of a fixed-point equation which describes the interdependence of the interference levels at neighboring base stations. Furthermore, we develop an efficient algorithm based on lognormal approximations to compute the mean and standard deviation of the othercell interference. We show that our model is accurate and fast enough to be used efficiently in the planning process of large UMTS networks.

The 3GPP standard proposes two methods to perform soft handover on the downlink. In the first one all base stations (BS) or node-B belonging to the active set (AS) transmit simultaneously to the mobile station (MS). All these signals are added at the MS using maximal ratio combining. The downlink power control adjusts the BS transmit powers such that the E/sub b/.N/sub o/ achieved by maximal ratio combining reaches the desired target E/sub b//N/sub o/. According to the 3GPP standard all BS in the AS transmit with an equal power to the MS. The other possibility to perform soft handover is called site selection diversity. In this case a single BS of the AS is selected and only this BS transmits to the MS while all other BS in the AS switch their power off. The advantage of this strategy is that the other BS in the AS produce no interference while the benefits of soft handover are maintained by fast site selection. If the radio link quality drops abruptly due to fading effects the MS can switch rapidly to another BS. In this paper we analytically compare the two methods with respect to the system capacity. Furthermore, we investigate soft handover mechanisms that allocate not necessarily equal proportions of the total power to the BS in the AS. These mechanism provide a compromise between equal power allocation and SSDT.

In this paper we investigate the impact of user distributions on the macro diversity gain in UMTS environments. Earlier studies indicated that macro diversity has a beneficial influence on the system capacity and coverage of WCDMA systems. However, these investigation were based on the assumption of evenly distributed traffic patterns. In practice rather clustered user distributions are experienced, thus, the study of uneven user distributions is of great importance to the planning of 3rd generation mobile networks. Using a Matern process to create clustered user point fields, the pair-correlation function is presented as a measure for this unevenness. Simulation studies are used to evaluate its impact on the macro-diversity gain in UMTS networks. Results prove the non-intuitive fact that the unevenness as found in reality helps to further improve the system capacity and coverage.

We develop an analytical expression far the mobile station transmit power based on a discrete time and state space. In our model we focus on the time-varying distortions found in a CDMA reverse link channel, network delays, and the fluctuations in multi-access interference. Based on this description we are able to characterize the dynamic behaviour of the power control loop and its reaction time to batch arrivals and departures. We also give an expression for exceeding the dynamic range of the discrete-step power control algorithm, allowing a systems engineer to calculate the trade-offs between capacity and coverage of the system.

An analytical model for dimensioning and planning of large UMTS networks with varying service mixtures is presented. Given the distribution of the UMTS traffic and the attenuation between mobiles and base stations using any given path loss prediction, the uplink-coverage probabilities and call blocking rates can be determined for a realistic "many cells-many mobiles" case. Because of effects like "cell breathing" a precise calculation of in-cell and inter-cell interference is done simultaneously. Imperfection of power control is taken into account. This analytical model permits fast calculations in particular for large networks.

We present an analytical model for computing the interference distribution in a third generation UMTS network. Our main focus lies on quantifying the interference reduction due to the combination of the power control signals from multiple base stations when the mobile stations are in soft handover. Our model also includes upper bounds of the mobile's transmission power, i.e. outage is considered. These effects influence the coverage areas and, therefore, play an important role in the planning of UMTS networks.

In this paper we examine the effects of Internet traffic on the quality of service (QoS) in GPRS wireless networks. With a stochastic source traffic model describing the user behavior, we will derive subjective and objective quality of service measures in terms of WWW downloading time and the transmission bandwidths on TCP and TBF level. Comparing the obtained values with wireline network modems and ISDN yields a slowdown factor which indicates the subjective degradation that the wireless user experiences.

The introduction of third generation (3G) wireless systems operating with Wideband Code Division Multiple Access (WCDMA) will offer new data services with bit rates of up to 2 Mbps and varying quality of service requirements in terms of received bit-energy-to-noise ratio. In order to reduce the interference in the cell and thus maximize the capacity WCDMA systems require a tight power control mechanism. In this paper we will present a performance evaluation of the WCDMA uplink power control loops by means of simulation. Our main goal is to investigate the influence of the traffic, given by the spatial user distribution and their data services, on the interference in a cell. We will also show that it is possible to use approximations of the power control loops to evaluate more complex scenarios.

In this paper we analyze the power control loops on the reverse link of a CDMA system. We obtain an expression for the transmission power of a mobile station and its signal-to-interference ratio (SIR) received at the base station. This allows the derivation of outage probability, which is the probability for not fulfilling the SIR requirements. We will show that power control in the North-American IS-95 system is very robust and that the number of users in the cell does not have much influence on outage. Furthermore, we compare outage which is an event at the receiver with the mobile station exceeding its maximum transmission power.

Recent measurement studies [8] have shown that peer-to-peer (P2P) file sharing applications are the major traffic source in the Internet. P2P applications, such as eDonkey, Kazaa, or BitTorrent, form overlay networks on the application layer and offer its peers to download and share their files with other peers in a highly distributed way. As a consequence, peers act simultaneously as both clients and servers. For a comprehensive survey of P2P technology, we refer to [7].

The performance of wireless sensor networks in terms of coverage, connectivity, lifetime and robustness is greatly influenced by the initial physical placement of the sensor nodes. In this paper we propose a novel deployment method for sensor nodes, when a large number of nodes is distributed from the air in a monitoring region that is inaccessible from the ground. In our deployment method, each sensor node is equipped with a parachute and a device to switch between its two falling behaviours (gliding and falling) in the air. After being dropped from midair, sensor nodes stochastically coordinate their falling behaviour in order to distribute themselves uniformly in the monitoring region. In addition, each sensor node exchanges messages with neighbouring nodes while being airborne and it changes its falling behaviour according to the density of the neighbouring nodes in order to reduce non-uniform areas. Through simulation evaluations, we confirm that our proposal can achieve a high uniformity in the placement of the nodes compared to a traditional airdrop method.

Several task forces are currently working on how to design the future Internet and it is high time for research work to also move a step forward to future mobile networks on a large scale. In this article, we propose a future mobile network management method based on a combination of OpenFlow and the biologically inspired attractor selection method to achieve scalability and energy efficiency. In other words, we propose novel approaches to wireless network management by extending the attractor selection mechanism in path and cluster management for signaling cost reduction. First, in path management, we establish a control method that each mobile node selects the best suited interfaces in accordance with instantaneous live traffic volume. Then, in cluster management, we design a network management method that network devices select the best OpenFlow cluster to join in order to reduce handover signaling cost. Through autonomous decisions of each mobile node and network device, the whole wireless network can be managed in an autonomous, energy efficient, and robust manner.

In this paper, we present ICEPT, a new mobile radio network planning tool that is based on an integrated design approach. The new approach starts with the analysis of the spatial distribution of the expected teletraffic within the service area of the cellular system. Employing this principle, the ICEPT tool considers concurrently the four major design areas of cellular networks: radio transmission, mobile subscriber, resource allocation, and system architecture. ICEPT uses these factors as input for the automatic network design algorithm ABPA which locates the base stations in the supplying area.