A contention-based access scheme, Distributed Coordination Function (DCF), is the basic access technology and it works as the basis for 802.11 MAC and its extensions. Using the Carrier-Sense Multiple Access with Collision Avoidance (CSMA/CA) mechanism and the Binary Exponential Backoff (BEB) mechanism, DCF can efficiently avoid multiple stations to transmit data at the same time and thus reduces the collision probability. In addition to BEB, Exponential Increase Exponential Decrease (EIED) is another well known backoff mechanism to avoid retransmission collision. In literature, many researches show that BEB algorithm may result in a poor throughput in a heavy load environment, while the EIED scheme does not perform as well as BEB under a light traffic condition. The emphasis of this paper is to address the shortcomings of the above two schemes and pose a solution to select a better random backoff timer in order to maximize the throughput under various traffic load. In this work, a novel backoff mechanism, Optimal Backoff (OB) mechanism, is proposed. OB can choose an optimal contention window according to current traffic conditions. Analytical and simulation results show that proposed Optimal Backoff mechanism always has highest throughput and lowest packet delay than those of the BEB and EIED mechanisms under both light and heavy traffic scenarios. With the deployment of the proposed OB, we believe that Wireless LAN is able to work perfectly as an extension of legacy mobile networks in t he context of upcoming Next Generation Networks.
Data collection is the most important stage in network forensics; but under the resource constrained situations, a good
evidence collection mechanism is required to provide effective event collections in a high network traffic environment.
In literatures, a few network forensic tools offer MSN-messenger behavior reconstruction. Moreover, they do not have
classification strategies at the collection stage when the system becomes saturated. The emphasis of this paper is to
address the shortcomings of the above situations and pose a solution to select a better classification in order to ensure the
integrity of the evidences in the collection stage under high-traffic network environments. A system-awareness decision
classifier (SADC) mechanism is proposed in this paper. MSN-shot sensor is able to adjust the amount of data to be
collected according to the current system status and to keep evidence integrity as much as possible according to the file
format and the current system status. Analytical results show that proposed SADC to implement selective collection (SC) consumes less cost than full collection (FC) under heavy traffic scenarios. With the deployment of the proposed SADC mechanism, we believe that MSN-shot is able to reconstruct the MSN-messenger behaviors perfectly in the context of upcoming next generation network.
Fast rerouting is a critical traffic engineering operation in the MPLS networks. To implement the Mobile IP service over the MPLS network, one can collaborate with the fast rerouting operation to enhance the availability and survivability. MPLS can protect critical LSP tunnel between Home Agent (HA) and Foreign Agent (FA) using the fast rerouting scheme. In this paper, we propose a simple but efficient algorithm to address the triangle routing problem for the Mobile IP over the MPLS networks. We consider this routing issue as a link weighting and capacity assignment (LW-CA) problem. The derived solution is used to plan the fast restoration mechanism to protect the link or node failure. In this paper, we first model the LW-CA problem as a mixed integer optimization problem. Our goal is to minimize the call blocking probability on the most congested working truck for the mobile IP connections. Many existing network topologies are used to evaluate the performance of our scheme. Results show that our proposed scheme can obtain the best performance in terms of the smallest blocking probability compared to other schemes.
In recent years, there has been tremendous interests and progresses in the field of wireless communications. Call admission control (CAC) is the key component to maximize the system utilization under certain QoS constraints such as call blocking rates. Among the CACs, Markov decision process (MDP) approach is a popular method to optimize certern objectives of interest. However, the computation complexity for deriving optimal policies make this approach less accessible to those with large problem size. In this paper, we will address this issue of how the optimal solutions fluctuate as the traffic condition changed using sensitivity analysis technique, in order to cut down unnecessary computing time if optimal policy did not change as the traffic conditions vary. First of all, the LP problem is solved by simplex method to examine the best policy when the optimal solution is found, then the sensitivity analysis technique is used by adding perturbation on traffic parameters to indicate the range to which optimal bases are invariant. The analytical results for computation complexity reduction is shown to analyze the performance under various traffic conditions.