Virtual reality (VR) is one of the applications with the most strict requirements in the performance of next generation networks, since it requires both high throughput, low delay, and packet loss. As the performance of networks, and the level of congestion varies over time, a need for adaptation in the stream’s data rate, in order to maintain reasonable packet loss, while using the available bandwidth, emerges. Motivated by this, in this contribution, we present an adaptation algorithm for VR applications, that exploits fuzzy logic, and transmission control protocol (TCP) transport in order to maintain the optimal data rate of the VR stream. In this direction, we perform a performance assessment of VR networks in the network simulator 3, that reveals that adaptation of the data rate is indeed necessary to provide the best possible VR data at the client. Moreover, it becomes evident that TCP transport, in combination with a data rate adaptation algorithm significantly reduces both the packet loss and the network delay, while maintaining high throughput. Finally, the proposed fuzzy algorithm outperforms well known adaptation algorithms in terms of throughput, delay and fairness.

In a multihop wireless network, it is crucial but challenging to schedule transmissions in an efficient and fair manner. In this paper, a novel distributed node scheduling algorithm, called Local Voting, is proposed. This algorithm tries to semi-equalize the load (defined as the ratio of the queue length over the number of allocated slots) through slot reallocation based on local information exchange. The algorithm stems from the finding that the shortest delivery time or delay is obtained when the load is semi-equalized throughout the network. In addition, we prove that, with Local Voting, the network system converges asymptotically toward the optimal scheduling. Moreover, through extensive simulations, the performance of Local Voting is further investigated in comparison with several representative scheduling algorithms from the literature. Simulation results show that the proposed algorithm achieves better performance than the other distributed algorithms in terms of average delay, maximum delay, and fairness. Despite being distributed, the performance of Local Voting is also found to be very close to a centralized algorithm that is deemed to have the optimal performance.

This paper is devoted to the approximate consensus problem for stochastic networks of nonlinear agents with switching topology, noisy, and delayed information about agent states. A local voting protocol with nonvanishing (e.g., constant) step size is examined under time-varying environments of agents. To analyze dynamics of the closed-loop system, the so-called method of averaged models is used. It allows us to reduce analysis complexity of the closed-loop stochastic system. We derive the upper bounds for mean square distance between states of the initial stochastic system and its approximate averaged model. These upper bounds are used to obtain conditions for approximate consensus achievement. An application of general theoretical results to the load balancing problem in stochastic dynamic networks with incomplete information about the current states of agents and with changing set of communication links is considered. The conditions to achieve the optimal level of load balancing are established. The performance of the system is evaluated both analytically and by simulation.

The MPEG-Dynamic Adaptation Streaming over HTTP (MPEG-DASH) tries to improve the quality perceived by the user by allowing the user's centric access to different resolutions of the video content via the Hypertext Transfer Protocol (HTTP). However, although it eliminates data packet loss, depending on the rate adaptation strategy adopted by the user, as well as, the network conditions, there may be playback interruptions. In this paper a novel MPEG-DASH adaptation scheme, the FDASH, is proposed, which, by employing fuzzy logic to control the buffering time and the resolution achieves the following: a) distributes the best possible resolution of video segments, b) delivers undisrupted video playback as a result of buffer underflows at the client, c) avoids unnecessary changes of video resolution owing to frequent fluctuations of the available connection throughput. Simulation results showed that the FDASH in comparison with other schemes succeeds in various network scenarios in providing the client with the best possible video rates avoiding buffer underflows and frequent changes of video resolution.

In this paper the authors propose a crowd coordination mechanism to increase the quality of articles produced in wiki systems. Wikis constitute promising social digital ecosystems for collaborative knowledge creation on the Web. However, as a result of the purely self-coordinated manner that they function, they cannot ensure the quality of the produced articles - an issue that affects their reliability and acceptance. The authors show that wiki article quality optimization can be formulated as a resource allocation problem. Contributors are selected from the wiki community crowd according to their skills, and matched to the articles they can improve the most. A model of the English Wikipedia is given, parameterized and validated from recent field studies results. Experimental results were obtained with simulation systems implementing this model and on a series of scenarios, which include an analysis of the impact of using semantic relations between wiki domains. The obtained results indicate that the proposed mechanism can lead to the production of wiki articles of higher quality, compared to the respective results achieved by the fully self-coordinated wiki.

Multihop networks are used in a variety of ways, that include ad-hoc networks, wireless sensor networks, and mesh networks. These networks consist of nodes that connect over a wireless channel, and communicate over multiple links by forwarding each other's messages. The throughput is determined by the contention among the nodes for the wireless resources. Thus routing algorithms, influence the level of contention at each location of the network, and play an important role in the network throughput. Additionally, the sequence of transmission opportunities of each node, which is determined by the scheduling algorithm, should also be carefully designed, since it affects the available resources of each node. In this paper we study the effect of routing and scheduling algorithms on the throughput of multihop networks. We propose a per-flow joint routing/scheduling algorithm that has the property of routing the flows in a way that avoids congested areas with limited availability, and also schedules links, in a way that a) slots are assigned to flows, instead of links or nodes, b) the assignment is fair c) fairness does not lead to underutilization. Simulation results showed that the proposed algorithm increases the average throughput, and the degree of satisfaction of each node, while at the same time it decreases the average delay.

In this paper, we present a framework for engineering collective intelligence systems that will be used by web communities. The proposed framework enables the development of communitydriven, self-regulating CI systems, which adapt their functionality to the activity and goals of the web community. The above engineering methodology is applied on the design of a popular web system, namely Wikipedia, to illustrate the way that the functionality of the latter could be improved, in terms of better and more prompt article quality production. The preliminary evaluation results of this application, obtained through simulation modeling are promising. Copyright 2010 ACM.

Collective intelligence (CI) is an emerging research field which aims at combining human and machine intelligence, to improve community processes usually performed by large groups. CI systems may be collaborative, like Wikipedia, or competitive, like a number of recently established problem-solving companies that attempt to find solutions to difficult R&D or marketing problems drawing on the competition among web users. The benefits that CI systems earn user communities, combined with the fact that they share a number of basic common characteristics, open up the prospect for the design of a general methodology that will allow the efficient development and evaluation of CI. In the present work, an attempt is made to establish the analytical foundations and main challenges for the design and construction of a generic collective intelligence system. First, collective intelligence systems are categorized into active and passive and specific examples of each category are provided. Then, the basic modeling framework of CI systems is described. This includes concepts such as the set of possible user actions, the CI system state and the individual and community objectives. Additional functions, which estimate the expected user actions, the future state of the system, as well as the level of objective fulfillment, are also established. In addition, certain key issues that need to be considered prior to system launch are also described. The proposed framework is expected to promote efficient CI design, so that the benefit gained by the community and the individuals through the use of CI systems, will be maximized. Copyright 2009 ACM.

TDMA has increasingly been used as the MAC layer for ad-hoc networks. However, the use of TDMA in multi-hop networks leads to the problem of distributing the available slots among the wireless nodes in an effective manner. The exact way the slots are distributed among the transmitting nodes has an impact on various performance parameters of the network, such as the end-to-end delay and the capacity. In general, an increase of the end-to-end delay may lead to an increased network capacity. In this paper, we study two new end-to-end TDMA scheduling algorithms, and compare them in terms of end-to-end delay and network capacity.

Medical broadband applications have attracted increased attention in the recent years. Also, the tremendous growth of wireless technologies has introduced the potential of continuous healthcare monitoring for mobile patients. The bandwidth requirements and the real-time nature of medical applications introduce the need for quality of service (QoS) provisioning in wireless broadband medical networks. Therefore, the use of Differentiated Services in Telemedicine forms a grand challenge. DiffServ may support a number of e-health applications with different traffic requirements, providing at the same time QoS guarantees. Resource Allocation in DiffServ for e-health application is inherently different in many aspects including the offered services, traffic requirements, propagation's characteristics and network structure. This paper presents a novel DiffServ architecture for QoS provisioning in emergency Telemedicine.