Fuzzy based load and energy aware multipath routing for mobile ad hoc networks

Routing is a challenging task in Mobile Ad hoc Networks (MANET) due to their dynamic topology and lack of central administration. As a consequence of un-predictable topology changes of such networks, routing protocols employed need to accurately capture the delay, load, available bandwidth and residual node energy at various locations of the network for effective energy and load balancing. This paper presents a fuzzy logic based scheme that ensures delay, load and energy aware routing to avoid congestion and minimise end-to-end delay in MANETs. In the proposed approach, forwarding delay, average load, available bandwidth and residual battery energy at a mobile node are given as inputs to a fuzzy inference engine to determine the traffic distribution possibility from that node based on the given fuzzy rules. Based on the output from the fuzzy system, traffic is distributed over fail-safe multiple routes to reduce the load at a congested node. Through simulation results, we show that our approach reduces end-to-end delay, packet drop and average energy consumption and increases packet delivery ratio for constant bit rate (CBR) traffic when compared with the popular Ad hoc On-demand Multipath Distance Vector (AOMDV) routing protocol

A genetic algorithm for the design of a fuzzy controller for active queue management

Active queue management (AQM) policies are those policies of router queue management that allow for the detection of network congestion, the notification of such occurrences to the hosts on the network borders, and the adoption of a suitable control policy. This paper proposes the adoption of a fuzzy proportional integral (FPI) controller as an active queue manager for Internet routers. The analytical design of the proposed FPI controller is carried out in analogy with a proportional integral (PI) controller, which recently has been proposed for AQM. A genetic algorithm is proposed for tuning of the FPI controller parameters with respect to optimal disturbance rejection. In the paper the FPI controller design metodology is described and the results of the comparison with random early detection (RED), tail drop, and PI controller are presented

Improving Context Interpretation by Using Fuzzy Policies: The Case of Adaptive Video Streaming

Best paper awardInternational audienceAdaptation is an increasingly important requirement for software systems executing in large-scale, heterogeneous, and dynamic environments. A central aspect of the adaptation methodology is management of contextual information needed to support the adaptation process. A major design challenge of managing contextual data lies in the fact that the information is partial, uncertain, and inherently suitable for diverging interpretations. While existing adaptation solutions focus on techniques, methods, and tools, the challenge of managing and interpreting ambiguous contextual information remains largely unresolved. In this paper we present a new adaptation approach that aims to overcome these issues by applying fuzzy set theory and approximate reasoning. We have defined a knowledge management scheme that allows the interpretation of imprecise information and effectively integrated it into the adaptation feedback control loop. To test and evaluate our solution, we implemented it in an adaptation engine to perform rate control for media streaming applications. We show the benefits of our approach in terms of flexibility and performance when compared to more traditional methods, such as TCP-friendly rate control

Quality of service control in IP networks using Fuzzy Logic for policy condition evaluation

This paper presents the architecture of a policy- based network management system designed specifically for Quality of Service management, where high level business policies are modeled as ECA (Event-Condition-Action) rules. Specifically, the system is mainly based on the policy architecture being proposed by the IETF (Internet Engineering Task Force), DMTF (Distributed Management Task Force), and TMF (TeleManagement Forum) standardization bodies. This work proposes a novel approach for policy condition evaluation using fuzzy logic. The fuzzy controller has the ability to examine policy conditions differently from default condition analyzers that employ simple conditions formed by a set of (IFs, ANDs and ORs), allowing the consideration and correlation of several input variables before taking decisions for the execution of policy actions. The system have been implemented and evaluated over a test bed network formed by Cisco® routers

Flow-oriented anomaly-based detection of denial of service attacks with flow-control-assisted mitigation

Flooding-based distributed denial-of-service (DDoS) attacks present a serious and major threat to the targeted enterprises and hosts. Current protection technologies are still largely inadequate in mitigating such attacks, especially if they are large-scale. In this doctoral dissertation, the Computer Network Management and Control System (CNMCS) is proposed and investigated; it consists of the Flow-based Network Intrusion Detection System (FNIDS), the Flow-based Congestion Control (FCC) System, and the Server Bandwidth Management System (SBMS). These components form a composite defense system intended to protect against DDoS flooding attacks. The system as a whole adopts a flow-oriented and anomaly-based approach to the detection of these attacks, as well as a control-theoretic approach to adjust the flow rate of every link to sustain the high priority flow-rates at their desired level. The results showed that the misclassification rates of FNIDS are low, less than 0.1%, for the investigated DDOS attacks, while the fine-grained service differentiation and resource isolation provided within the FCC comprise a novel and powerful built-in protection mechanism that helps mitigate DDoS attacks

A machine learning-based framework for preventing video freezes in HTTP adaptive streaming

HTTP Adaptive Streaming (HAS) represents the dominant technology to deliver videos over the Internet, due to its ability to adapt the video quality to the available bandwidth. Despite that, HAS clients can still suffer from freezes in the video playout, the main factor influencing users' Quality of Experience (QoE). To reduce video freezes, we propose a network-based framework, where a network controller prioritizes the delivery of particular video segments to prevent freezes at the clients. This framework is based on OpenFlow, a widely adopted protocol to implement the software-defined networking principle. The main element of the controller is a Machine Learning (ML) engine based on the random undersampling boosting algorithm and fuzzy logic, which can detect when a client is close to a freeze and drive the network prioritization to avoid it. This decision is based on measurements collected from the network nodes only, without any knowledge on the streamed videos or on the clients' characteristics. In this paper, we detail the design of the proposed ML-based framework and compare its performance with other benchmarking HAS solutions, under various video streaming scenarios. Particularly, we show through extensive experimentation that the proposed approach can reduce video freezes and freeze time with about 65% and 45% respectively, when compared to benchmarking algorithms. These results represent a major improvement for the QoE of the users watching multimedia content online

Fuzzy Based Vertical Handoff Decision Controller for Future Networks

— In Next generation wireless Networks, the received signals (RSS) from different networks do not have a same meaning since each network is composed of its specific characteristics and there is no common pilot signal. Then, RSS comparisons are insufficient for handoff decision and may be inefficient and impractical. A more complex decision criterion that combines a large number of parameters or factors such as monetary cost, bandwidth, and power consumption and user profile is necessary. Though there are a lot works available for vertical handoff decision (VHD) for wireless networks, the selection of best network is still challenging problem. In this paper we propose a Fuzzy based vertical handoff decision controller (FVHDC) Which performs handover decision based on the output of fuzzy based rules

Handover in Mobile Wireless Communication Network - A Review

Mobility is the characteristics of mobile communication that makes it irresistible by all and sundry. The whole world is now engaging in wireless communication as it provides users\u27 ability to communicate on-the-go. This is achieved by transferring users from a radio network to another. This process is called handover. Handover occurs either by cell crossing or by deterioration in signal quality of the current channel. The continuation of an active call is a critical characteristic in cellular systems. Brief overview of handover, handover type, commonly used handover parameters, some methods employed in the literature and we present the convergent point for furtherance in the area of mobile wireless communication Handover