Changing Network Conditions Research Articles

A Game-Theoretic Approach for Dynamic and Adaptive Managers Selection in Service Specific Overlay Networks

The introduction of Service Overlay Networks (SON) enabled service providers to offer new services with end-to-end quality of service guarantees. As a consequence, modern networks have become more service centric, which require the application of service specific management approaches. However, increased heterogeneity of network components and access technologies made management tasks more tedious and complex. In this article, we propose the use of game theory in the management tasks of overlay networks to reduce cost and complexity. We propose a fully distributed, self-organizing, and self-adapting algorithm for overlay nodes to efficiently select their managers. The proposed algorithm copes with the highly decentralized and dynamic nature of SON and adapts to changing network conditions. Extensive simulation results validate the effectiveness of the approach compared to existing solutions and the optimal solution.

Dynamic Trust Management for Delay Tolerant Networks and Its Application to Secure Routing

Delay tolerant networks (DTNs) are characterized by high end-to-end latency, frequent disconnection, and opportunistic communication over unreliable wireless links. In this paper, we design and validate a dynamic trust management protocol for secure routing optimization in DTN environments in the presence of well-behaved, selfish and malicious nodes. We develop a novel model-based methodology for the analysis of our trust protocol and validate it via extensive simulation. Moreover, we address dynamic trust management, i.e., determining and applying the best operational settings at runtime in response to dynamically changing network conditions to minimize trust bias and to maximize the routing application performance. We perform a comparative analysis of our proposed routing protocol against Bayesian trust-based and non-trust based (PROPHET and epidemic) routing protocols. The results demonstrate that our protocol is able to deal with selfish behaviors and is resilient against trust-related attacks. Furthermore, our trust-based routing protocol can effectively trade off message overhead and message delay for a significant gain in delivery ratio. Our trust-based routing protocol operating under identified best settings outperforms Bayesian trust-based routing and PROPHET, and approaches the ideal performance of epidemic routing in delivery ratio and message delay without incurring high message or protocol maintenance overhead.

Coping with Network Dynamics Using Reinforcement Learning Based Network Optimization in Wireless Sensor Networks

Due to the constant increase of in density of wireless network devices, inter-network cooperation is increasingly important. To avoid conflicts, advanced algorithms for inter-network optimization utilize cognition processes such as reinforcement learning to enable networks to become capable of solving complex optimization problems on their own with minimal outside intervention. This paper investigates the inherent trade-offs that occur when using reinforcement learning techniques in dynamic networks: the need to keep the network running optimally whilst, at the same time, different (suboptimal) network settings need to be continuously investigated to cope with changing network conditions. To cope with these network dynamics, two existing algorithms, epsilon greedy and Softmax, are compared to a novel approach, based on a logarithmic probability distribution function. It is shown that, depending on the expected level of dynamics, the new algorithm outperforms existing solutions.

Reachability Analysis for the Verification of Adaptive Protection Setting Selection Logic

The testing of adaptive protection schemes is a problem that remains largely unaddressed. These schemes can be characterized by uncertainty in behavior due to the dynamic changes in their configuration to suit prevailing network conditions. This paper proposes a novel approach to formalizing this behavior using hybrid systems modeling. This unlocks the ability to verify the safety performance of the schemes using reachability analysis. In this paper, an adaptive setting selection logic for distance protection is verified for its safety, using reachability analysis, during changes in network conditions.

An Energy-Efficient QoS-aware Routing Algorithm for Wireless Multimedia Sensor Networks

Sensor nodes in WMSNs should be able to collect various forms of sensing data, prioritize each form of data based on the application service request conditions, and provide a certain degree of Quality of Service (QoS) guarantee. In order for sensor nodes to provide QoS, they must maintain routing information based on delay, reliability, and energy efficiency. Existing routing algorithms transmit many routing control messages to reflect dynamic network conditions. In this paper, we propose a routing protocol that can provide QoS that appropriately reflects changes in network status regarding reliability and delay, even in circumstances with a deficiency in sensor node resources. Our algorithm has the advantage of minimizing the routing control messages and therefore can safely operate from an energyefficient perspective, as the algorithm utilizes broadcast messages regularly transmitted by the sink node. We observe that the sensor node establishes a routing table based on the shortest route towards a sink, the energy efficiency of the foothold, and the least amount of congestion

Quality of Information and Energy Efficiency Optimization for Sensor Networks via Adaptive Sensing and Transmitting

Co-optimizing information quality and energy efficiency are an important but challenging problem in sensor networks, because of the interdependency that exists between them. For example, increasing sensor sampling rate will improve information quality but cost energy consumption, due to more traffic needed to be transmitted. To address this co-optimization issue, this paper first presents a novel quality/energy efficient metric, which models the relationship of sensing, processing, and transmitting with quality and energy. Then, based on the metrics, a quality-energy adapting system is developed to exploit base station scheduling priority and techniques such as batch processing and adaptive sampling to optimize both energy efficiency and overall quality. Our results have demonstrated the usefulness of this model and its feasibility for base station to runtime co-optimize both quality and energy under changing environment and network conditions.

Improving Fairness, Efficiency, and Stability in HTTP-Based Adaptive Video Streaming With Festive

Modern video players today rely on bit-rate adaptation in order to respond to changing network conditions. Past measurement studies have identified issues with today's commercial players when multi...

Improving Fairness, Efficiency, and Stability in HTTP-Based Adaptive Video Streaming With Festive

Modern video players today rely on bit-rate adaptation in order to respond to changing network conditions. Past measurement studies have identified issues with today's commercial players when multiple bit-rate-adaptive players share a bottleneck link with respect to three metrics: fairness, efficiency, and stability. Unfortunately, our current understanding of why these effects occur and how they can be mitigated is quite limited. In this paper, we present a principled understanding of bit-rate adaptation and analyze several commercial players through the lens of an abstract player model consisting of three main components: bandwidth estimation, bit-rate selection, and chunk scheduling. Using framework, we identify the root causes of several undesirable interactions that arise as a consequence of overlaying the video bit-rate adaptation over HTTP. Building on these insights, we develop a suite of techniques that can systematically guide the tradeoffs between stability, fairness, and efficiency and thus lead to a general framework for robust video adaptation. We pick one concrete instance from this design space and show that it significantly outperforms today's commercial players on all three key metrics across a range of experimental scenarios.

Playout Scheduling Method Based on Adaptive Jitter Estimation for Enhancing VoIP Speech Quality

지터라고 불리는 패킷 도착 지연의 편차는 모바일 단말기에서 Voice over Internet Protocol (VoIP)음성의 품질을 저하시키는 주요한 원인 중 하나이다. 이 문제를 해결하기 위해서 본 논문에서는 VoIP 음질향상을 위한 적응적 지터추정 기반의 플레이아웃 스케줄링 방법을 제안한다. 제안된 알고리즘은 예측된 네트워크 지연의 변화에 따라 각각의 패킷을 신장 혹은 압축하여 전송 지터의 영향에 대응한다. 이와 함께, 네트워크 지터 추정은 신속한 지연 스파이크 검출과 네트워크 상태 변화에 대한 반응을 포함한다. 실험결과는 제안된 알고리즘이 불안정한 네트워크 환경에서 고음질을 제공하는 것을 보여 주었다. Packet arrival-delay variation, so-called 'jitter' is one of the main factors that degrade the quality of voice in mobile devices at the Voice over Internet Protocol (VoIP). To resolve this issue, a playout scheduling based on adaptive jitter estimation for enhancing VoIP speech quality is proposed. The proposed algorithm copes with the effect of transmission jitter by expanding or compressing each packet according to the predicted network delay and variations. Additionally, the active network jitter estimation incorporates rapid detection of delay spikes and reacts to changes in network conditions. The experimental results have shown that the proposed algorithm delivers high voice quality in unstable network environment.

Route maintenance and Scalability improvement of DSR, based on Relay node identification after locating Link-failure over MANET

In Dynamic Source Routing, each source determines the route to be used in transmitting its packets to destination. Route Discovery determines the optimum path for a transmission between a given source and destination. Route Maintenance ensures that the transmission path remains optimum and loop-free as network conditions change, even if this requires changing the route during a transmission. Many protocols were proposed to maintain route from high data loss and transition delay due to frequent link failure but doesn't take the decision on basis of location of failure link in source route and also doesn't take advantages of Relay node identification in partitioned source route. From this point of view in our paper we propose an algorithm with the help of local link repairing and improvement strategy based on the location of link failure inside source route over mobile ad- hoc network. Through this paper we introduce our proposed approach based on DSR, which takes decision on the basis of the location of Relay node(where link failure is detected) in source route.We think our new approach can be able to improve packet salvaging, packet delivery ratio and reducing end to end delay to improve the scalability of Mobile Ad-hoc network.

ZNA: A Six-Layer Network Architecture for New Generation Networks —— Focusing on the Session Layer, the Network Layer, and Cross-Layer Cooperation ——

Using “clean-slate approach” to redesign the Internet has attracted considerable attention. ZNA (Z Network Architecture) is one of clean-slate network architectures based on the layered model. The major features of ZNA are as follows: (1) introducing the session layer to provide the applications with sophisticated communication services, (2) employing inter-node cross-layer cooperation to adapt to the dynamically changing network conditions, (3) splitting the node identifier and the node locator for mobility, multi-homing, and heterogeneity of network layer protocols, (4) splitting the data plane and the control plane for high manageability, and (5) introducing a recursive layered model to support network virtualization. This paper focuses on the first three topics as well as the basic design of ZNA.

Integration of Direction Cues Is Invariant to the Temporal Gap between Them

Many decisions involve integration of evidence conferred by discrete cues over time. However, the neural mechanism of this integration is poorly understood. Several decision-making models suggest that integration of evidence is implemented by a dynamic system whose state evolves toward a stable point representing the decision outcome. The internal dynamics of such point attractor models render them sensitive to the temporal gaps between cues because their internal forces push the state forward once it is dislodged from the initial stable point. We asked whether human subjects are as sensitive to such temporal gaps. Subjects reported the net direction of stochastic random dot motion, which was presented in one or two brief observation windows (pulses). Pulse strength and interpulse interval varied randomly from trial to trial. We found that subjects' performance was largely invariant to the interpulse intervals up to at least 1 s. The findings question the implementation of the integration process via mechanisms that rely on autonomous changes of network state. The mechanism should be capable of freezing the state of the network at a variety of firing rate levels during temporal gaps between the cues, compatible with a line of stable attractor states.

Dynamic eICIC — A Proactive Strategy for Improving Spectral Efficiencies of Heterogeneous LTE Cellular Networks by Leveraging User Mobility and Traffic Dynamics

Enhanced Inter-cell Interference Co-ordination (eICIC) is a time-domain multiplexing technique for improving the performance of legacy co-channel Heterogeneous Networks (HetNets). eICIC offers several benefits, including a more equitable distribution of user traffic across the macro and embedded pico cells (i.e., load balancing), in turn leading to better pico cell utilizations and better edge user throughputs. eICIC uses two mechanisms to achieve load balancing: (i) a cell selection bias to increase the pico coverage area, enabling the pico to attract more users, and (ii) macro muting ("Almost Blank Sub-frame", ABS) to improve SINRs of range extended pico users. Network load in the cellular system varies continuously as a result of user mobility and traffic dynamics (the varying amount of data pending for a user - arising from packet arrivals and eventual departures). Previous work did not consider dynamically changing network conditions in HetNets. Hence, they studied the benefits of eICIC over legacy HetNets arising from static optimization of eICIC parameters. Our approach is dynamic, and further improves performance by keeping the HetNet continuously optimized for improved user experience, by adapting the ABS in response to dynamic variations in network load. We present several analytical formulations, which allow for simple optimizations and an intuitive understanding of the desired system response to load variation. Exhaustive system simulations illustrate the performance gains along different dimensions, such as spectral efficiency, fairness, mean file transfer times, number of file transmissions, number of file drops, and mean queue lengths. Furthermore, we study the impact of different mobility scenarios, traffic mixes, and adaptation rate. We also provide a brief discussion of practical considerations in implementing Dynamic eICIC.

Adaptive controller placement for wireless sensor–actuator networks with erasure channels

Wireless sensor–actuator networks offer flexibility for control design. One novel element which may arise in networks with multiple nodes is that the role of some nodes does not need to be fixed. In particular, there is no need to pre-allocate which nodes assume controller functions and which ones merely relay data. We present a flexible architecture for networked control using multiple nodes connected in series over analog erasure channels without acknowledgments. The control architecture proposed adapts to changes in network conditions, by allowing the role played by individual nodes to depend upon transmission outcomes. We adopt stochastic models for transmission outcomes and characterize the distribution of controller location and the covariance of system states. Simulation results illustrate that the proposed architecture has the potential to give better performance than limiting control calculations to be carried out at a fixed node.

Skyline-Based Aggregator Node Selection in Wireless Sensor Networks

In order to achieve the equal usage of limited resources in the wireless sensor networks (WSNs), we must aggregate the sensor data before passing it to the base station. In WSNs, the aggregator nodes perform a data aggregation process. Careful selection of the aggregator nodes in the data aggregation process results in reducing large amounts of communication traffic in the WSNs. However, network conditions change frequently due to sharing of resources, computation load, and congestion on network nodes and links, which makes the selection of the aggregator nodes difficult. In this paper, we study an aggregator node selection method in the WSNs. We formulate the selection process as a top-k query problem, where we efficiently solve the problem by using a modified Sort-Filter-Skyline (SFS) algorithm. The main idea of our approach is to immediately perform a skyline query on the sensor nodes in the WSNs, which enables to extract a set of sensor nodes that are potential candidates to become an aggregator node. The experiments show that our method is several times faster compared to the existing approaches.

Mobile video optimization at the base station: Adaptive guaranteed bit rate for HTTP adaptive streaming

Video is expected to be the dominant application by traffic volume over mobile networks in the near future. Mobile network operators are deploying video optimization techniques to enhance the user experience and network utilization for video delivery. Video optimization is typically “out-of-network” and includes techniques such as transcoding, transrating, time shifting and pacing that are implemented outside of mobile radio access and core networks. However, such techniques cannot easily exploit information about real time cell congestion and radio conditions for the video terminals because it is difficult to obtain such information from the radio access network. We propose a novel “in-network” video optimization technique, named Adaptive Guaranteed Bit Rate (AGBR), for HTTP-based Adaptive Streaming (HAS) video. This optimization technique is implemented at the base station and can thus exploit knowledge of the radio and congestion conditions. With only limited knowledge of the video stream properties or content, AGBR works by adjusting the throughput delivered to the different HAS clients that in turn adjust the video quality they request. The optimization algorithm maximizes aggregate quality across multiple video flows served by the base station without starving data clients, thereby improving the overall quality of experience. We demonstrate through extensive analytical modeling and simulations that AGBR can adapt to changing network conditions to support more video sessions at an acceptable quality than alternative algorithms, while enforcing fairness among all users competing for resources within a sector.

A combined framework for modeling the evolution of traveler route choice under risk

The paper develops a new framework to model the evolution of traveler route choice under risk. It embeds prospect theory in the replicator dynamics (RD), so as to allow for individual decision behavior while investigate the network state change at the population level. First, the new model is put forward based on a linear piecewise value function, in a two-route network. Some conclusions about the equilibrium states are discussed. Second, four models are formulated in a three-route network, to investigate the day-to-day route choice evolutions under the prospect assumptions. The new framework achieves average travel times no worse than the Expected Utility Theory-based RD framework, significant route switches occur at the same time. The effect of the reference point values are investigated, robust or even tiny bettering-off in average travel times still hold. Obvious route switches occur merely when the reference points fall in a certain interval. Then, taking the fourth model (M4) as an example, the sensitivities of some parameter (-combinations) are examined, the possible implications are discussed. The new framework shows flexibility in incorporating different factors in relation to individual bounded rationality and population dynamics. The possible applications may involve modeling group choice evolutions in occurrence of unexpected incidents, from the aspect of individual risk attitude, perception and decision schemes. Some limitations of the proposed framework and other research opportunities are discussed.

Motor Cortex Feedback Influences Sensory Processing by Modulating Network State

Long-range corticocortical communication may have important roles in context-dependent sensory processing, yet we know very little about how these pathways influence their target regions. We studied the influence of primary motor cortex activity on primary somatosensory cortex in the mouse whisker system. We show that primary motor and somatosensory cortices undergo coherent, context-dependent changes in network state. Moreover, we show that motor cortex activity can drive changes in somatosensory cortex network state. A series of experiments demonstrate the involvement of the direct corticocortical feedback pathway, providing temporally precise and spatially targeted modulation of network dynamics. Cortically mediated changes in network state significantly impact sensory coding, with activated states increasing the reliability of responses to complex stimuli. By influencing network state, corticocortical communication from motor cortex may ensure that during active exploration the relevant sensory region is primed for enhanced sensory discrimination.

Research on a Method of Service-Oriented Network Layer Network Security Situation Assessment

The purpose of this study is to obtain the running situation of the network service accurately and efficiently, and then to perceive the overall security situation of the network. Simultaneity, find the potential agressire behavior and abnormal status. A service-oriented approach is presented. After establishing an evaluation index system at the network level, extracting the momentum factors, we use fuzzy AHP combining with evidence theory for real-time evaluation of network security situation to get the running situation of the network service, and then to evaluate the overall security situation of the network, identify potential attacks and network anomalies, help network policy makers take positive action and avoid to cause irreparable serious consequences. Experimental data show that the network security posture assessment results can be sensitive to changes in network status and accurately reflect the status of the network's security situation.

Streaming 3D meshes over thin mobile devices

We are witnessing a significant growth in applications using thin mobile devices, such as social networks, virtual walkthrough, massively multiplayer online gaming (MMOG), and augmented reality (AR), just to mention a few. Virtual environments (VE) based class of applications have recently attracted a large number of users. Applications that applied the conventional client-server architecture require the VE to be stored on the client, which is not very feasible due to the client's memory constraints. To address this issue, 3D streaming techniques have been designed and are widely used nowadays. However, several challenges exist and affect the user's Quality of Experience (QoE). By all means, these challenges need to be resolved before the 3D streaming technology over thin mobile devices becomes a commodity. In this paper, we provide a survey on the existing 3D streaming techniques by classifying them based on the nature of the application, and we centralize our attention on methods applied to adapt 3D streaming techniques to the changes in the wireless network conditions. Therefore, we discuss the challenges that the 3D streaming techniques face from a network point of view, as well as the approaches and solutions proposed.