An Artificial Immune System for Misbehavior Detection in Mobile Ad-Hoc Networks with Virtual Thymus, Clustering, Danger Signal and Memory Detectors

In mobile ad-hoc networks, nodes act both as terminals and information relays, and participate in a common routing protocol, such as Dynamic Source Routing (DSR). The network is vulnerable to routing misbehavior, due to faulty or malicious nodes. Misbehavior detection systems aim at removing this vulnerability. For this purpose, we use an Artificial Immune System (AIS), a system inspired by the human immune system (HIS). Our goal is to build a system that, like its natural counterpart, automatically learns and detects new misbehavior. In this paper we build on our previous work and investigate the use of four concepts: (1

Distribution of on line Contents on Servers with GA Approach

ABSTRACT: All the traffic seen by the internet is treated equally which is generally known as Internet neutrality. Internet Neutrality enforces that all network traffic should be treated as equal and Best effort routing policy should be followed. But with the advent of smart applications this is drastically changing. Each network application has its own bandwidth requirement. We face the problem when required bandwidth of critical applications does not match with internet bandwidth. Because of network neutrality principle, core router can't priorities one traffic over other and critical applications may get impacted. Such types of problems are still in re-search phase As a solution here we will see how application level routing optimization mechanism with GA approach at edge routers can be useful for such types of application

Network protection with guaranteed recovery times using recovery domains

We consider the problem of providing network protection that guarantees the maximum amount of time that flow can be interrupted after a failure. This is in contrast to schemes that offer no recovery time guarantees, such as IP rerouting, or the prevalent local recovery scheme of Fast ReRoute, which often over-provisions resources to meet recovery time constraints. To meet these recovery time guarantees, we provide a novel and flexible solution by partitioning the network into failure-independent “recovery domains”, where within each domain, the maximum amount of time to recover from a failure is guaranteed. We show the recovery domain problem to be NP-Hard, and develop an optimal solution in the form of an MILP for both the case when backup capacity can and cannot be shared. This provides protection with guaranteed recovery times using up to 45% less protection resources than local recovery. We demonstrate that the network-wide optimal recovery domain solution can be decomposed into a set of easier to solve subproblems. This allows for the development of flexible and efficient solutions, including an optimal algorithm using Lagrangian relaxation, which simulations show to converge rapidly to an optimal solution. Additionally, an algorithm is developed for when backup sharing is allowed. For dynamic arrivals, this algorithm performs better than the solution that tries to greedily optimize for each incoming demand.National Science Foundation (U.S.) (NSF grant CNS-1017800)National Science Foundation (U.S.) (grant CNS-0830961)United States. Defense Threat Reduction Agency (grant HDTRA-09-1-005)United States. Defense Threat Reduction Agency (grant HDTRA1-07-1-0004)United States. Air Force (Air Force contract # FA8721-05-C-0002

Recursive Loop-Free Alternates for full protection against transient link failures

In this paper, we propose a routing technique, “recursive Loop-Free Alternates (rLFAs)”, to alleviate packet loss due to transient link failures. The technique consists of a backup path calculation with corresponding re-routing scheme based on the Loop-Free Condition (LFC) as defined in the basic specification for IP Fast Re-Route (IPFRR). Under this routing strategy, nodes calculate backup paths by modifying the weights of links in the primary shortest path tree. If a failure occurs, the detecting node determines the number of recursions, which indicates the number of times packets must be forwarded along the alternate next hops to bypass the failed link. This technique guarantees full repair coverage for single link failures. We evaluate the performance of our proposed technique through simulations and show that the incurred overheads, the stretch of its pre-computed alternate paths, and the failure-state Maximum Link Utilisation (MLU) are minimal

Smart routing: towards proactive fault handling of software-defined networks

In recent years, the emerging paradigm of software-defined networking has become a hot and thriving topic in both the industrial and academic sectors. Software-defined networking offers numerous benefits against legacy networking systems by simplifying the process of network management through reducing the cost of network configurations. Currently, data plane fault management is limited to two mechanisms: proactive and reactive. These fault management and recovery techniques are activated only after a failure occurrence and hence packet loss is highly likely to occur. This is due to convergence time where new network paths will need to be allocated in order to forward the affected traffic rather than drop it. Such convergence leads to temporary service disruption and unavailability. Practically, not only the speed of recovery mechanisms affects the convergence, but also the delay caused by the process of failure detection. In this paper, we define a new approach for data plane fault management in software-defined networks where the goal is to eliminate the convergence process altogether rather than accelerate the failure detection and recovery. We propose a new framework, called Smart Routing, which allows the network controller to receive forewarning signs on failures and hence avoid risky paths before the failure incidents occur. The proposed approach aims to decrease service disruption, which in turn increases network service availability. We validate our framework through a set of experiments that demonstrate how the underlying model runs and its impact on improving service availability. We take as example of the applicability of the new framework three types of topologies covering real and simulated networks

Real-time bandwidth encapsulation for IP/MPLS Protection Switching

Bandwidth reservation and bandwidth allocation are needed to guarantee the protection of voice traffic during network failure. Since voice calls have a time constraint of 50 ms within which the traffic must be recovered, a real-time bandwidth management scheme is required. Such bandwidth allocation scheme that prioritizes voice traffic will ensure that the voice traffic is guaranteed the necessary bandwidth during the network failure. Additionally, a mechanism is also required to provide the bandwidth to voice traffic when the reserved bandwidth is insufficient to accommodate voice traffic. This mechanism must be able to utilise the working bandwidth or bandwidth reserved for lower priority applications and allocate it to the voice traffic when a network failure occurs

SWIFT: Predictive Fast Reroute

Network operators often face the problem of remote outages in transit networks leading to significant (sometimes on the order of minutes) downtimes. The issue is that BGP, the Internet routing protocol, often converges slowly upon such outages, as large bursts of messages have to be processed and propagated router by router. In this paper, we present SWIFT, a fast-reroute framework which enables routers to restore connectivity in few seconds upon remote outages. SWIFT is based on two novel techniques. First, SWIFT deals with slow outage notification by predicting the overall extent of a remote failure out of few control-plane (BGP) messages. The key insight is that significant inference speed can be gained at the price of some accuracy. Second, SWIFT introduces a new data-plane encoding scheme, which enables quick and flexible update of the affected forwarding entries. SWIFT is deployable on existing devices, without modifying BGP. We present a complete implementation of SWIFT and demonstrate that it is both fast and accurate. In our experiments with real BGP traces, SWIFT predicts the extent of a remote outage in few seconds with an accuracy of ~90% and can restore connectivity for 99% of the affected destinations

High Availability in the Future Internet

With the evolution of the Internet, a huge number of real- time applications, like Voice over IP, has started to use IP as primary transmission medium. These services require high availability, which is not amongst the main features of today’s heterogeneous Internet where fail- ures occur frequently. Unfortunately, the primary fast resilience scheme implemented in IP routers, Loop-Free Alternates (LFA), usually does not provide full protection against failures. Consequently, there has been a growing interest in LFA-based network optimization methods, aimed at tuning some aspect of the underlying IP topology to maximize the ratio of failure cases covered by LFA. The main goal of this chapter is to give a comprehensive overview of LFA and survey the related LFA network op- timization methods, pointing out that these optimization tools can turn LFA into an easy-to-deploy yet highly effective IP fast resilience scheme

Balancing Performance, Robustness and Flexibility in Routing Systems

Modern networks face the challenging task of handling increasingly diverse traffic that is displaying a growing intolerance to disruptions. This has given rise to many initiatives, and in this paper we focus on multiple topology routing as the primary vehicle for meeting those demands. Specifically, we seek routing solutions capable of not just accommodating different performance goals, but also preserving them in the presence of disruptions. The main challenge is computational, i.e., to identify among the enormous number of possible routing solutions the one that yields the best compromise between performance and robustness. This is where our principal contribution lies, as we expand the definition of critical links -- a key concept in improving the efficiency of routing computation -- and develop a precise methodology to efficiently converge on those solutions. Using this new methodology, we demonstrate that one can compute routing solutions that are both flexible in accommodating different performance requirements and robust in maintaining them in the presence of failures and traffic fluctuations