Huaqiang Yuan

Initiative movement prediction assisted adaptive handover trigger scheme in fast MIPv6

Roaming across two adjacent access networks poses a challenging issue in providing continuity services for end-users. FMIPv6, a cross layer handover scheme proposed by the IETF, requires the timely link layer (L2) trigger to invoke the handover protocols of upper layer, the specified handover procedures hence can be completed before terminating the current wireless link. Generating the L2 trigger however is not always preferable by experimental analysis. The premature L2 trigger leads to a false alarm and unnecessary handover operations with serious performance loss and resources waste. By analyzing the movement behavior of the mobile node (MN), an initiative movement predictive algorithm is developed to predict the movement trend of the MN, and an adaptive handover trigger scheme (IMP-AHT) taken as the supplement for FMIPv6 is proposed accordingly. IMP-AHT addresses the investigation on rational decision of generating L2 trigger reliably. Owing to the inevitably introduced errors of the prediction process, some effective measures are also introduced to compensate the degraded performance caused by the false decisions. Simulations will compare as well as analyze IMP-AHT and FMIPv6 to evaluate the efficiency.

Constrained differential evolution using generalized opposition-based learning

Differential evolution (DE) is a well-known optimization approach to deal with nonlinear and complex optimization problems. However, many real-world optimization problems are constrained problems that involve equality and inequality constraints. DE with constraint handling techniques, named constrained differential evolution (CDE), can be used to solve constrained optimization problems. In this paper, we propose a new CDE framework that uses generalized opposition-based learning (GOBL), named GOBL-CDE. In GOBL-CDE, firstly, the transformed population is generated using general opposition-based learning in the population initialization. Secondly, the transformed population and the initial population are merged and only half of the best individuals are selected to compose the new initial population to proceed mutation, crossover, and selection. Lastly, based on a jumping probability, the transformed population is calculated again after generating new populations, and the fittest individuals are selected to compose new population from the union of the current population and the transformed population. The GOBL-CDE framework can be applied to most CDE variants. As examples, in this study, the framework is applied to two popular representative CDE variants, i.e., rank-iMDDE and

SmartHO: mobility pattern recognition assisted intelligent handoff in wireless overlay networks

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Cooperative Routing for Multi-flow Wireless Sensor Networks

εDEag. Experiment results on 24 benchmark functions from CEC’2006 and 18 benchmark functions from CEC’2010 show that the proposed framework is an effective approach to enhance the performance of CDE algorithms.

Version-vector based video data online cloud backup in smart campus

Multi-level mobile anchor points (MAP) architecture is deployed in large-scale wireless/mobile networks using HMIPv6 to achieve better mobility service, while selecting the most suitable serving MAP for the mobile nodes (MNs) to enhance the whole network performance has been a critical issue. An adaptive MAP selection based on active overload prevention (MAP-AOP) hence is proposed. The MAP periodically evaluates the load status by using dynamic weighted load evaluation algorithm, and then sends the load information to the covered access routers (AR) by using the expanded routing advertisement message in a dynamic manner. Taking achieving the load balancing among the available MAPs, the current serving AR executes the active overload prevention to select MAP candidates for the MN pending a handover, and then adaptively selects an optimal one from the candidates by comprehensively considering the system cost and the average handover latency caused by each candidate. The simulation conducted on the NS-2 platform indicates that MAP-AOP outperforms the comparative MAP selection schemes with the optimized system cost and average handover latency, and better load balancing.

Joint Topology Control and Channel Assignment Employing Partially Overlapping Channels in Multirate Wireless Mesh Backbone

Handoff management providing continuous mobility services is important for end-users in wireless overlay networks. The existing studies focus on improving the handoff performance with little attention to determine the current mobility pattern to provide different advanced services for end-users, and the handoff process is not intelligent as well. Due to the randomness and fuzziness of human mobility, predicting the mobility is still an open issue. In this paper, a mobility pattern recognition assisted intelligent handoff (SmartHO) is proposed. By exploring the regularity and rationality in the seemingly random daily itinerary and analyzing the typical mobility patterns, a spatial–temporal mobility pattern model is firstly constructed, and the mobility pattern recognition algorithm based on the joint space–time correlation then is designed. In different handoff cases, the specific handoff optimization strategies corresponding to the mobility patterns are employed to make the handoff process more intelligent. With the configurations from the authors real life, the simulations conducted on the NS-2 platform show that SmartHO outperforms FHMIPv6 in the critical handoff performance metrics.

Movement prediction assisted timely L2 trigger in FMIPv6

Addressing the energy efficiency in data-centric and application-oriented wireless sensor networks is an eternal theme, and in the practical scenarios deployed multiple flows, often a serious problem of collisions among multiple paths caused by the fierce network resource competition directly influences the whole network performance. To address this issue, in terms of the delay sensitivity imposed on the deployed flows, a feature-aware cooperative relay selection scheme is developed by comprehensively taking both the routing selection and contention avoidance into account, in which the concept of abstract domain is introduced to extend the covered relay nodes. The optimal relays for the deployed multiflow with specific probing and transmission requirements are selected to find collision-free and energy-efficient cooperative routings. Simulations conducted on NS-2 platform demonstrate that the proposed cooperative routing outperforms the compared routing selection strategies in significantly balancing the energy distribution and prolonging the network lifetime.

Performance Compensation for the False Alarm of L2 Trigger in FMIPv6

In data-centric and application-oriented Wireless Sensor Network, effective energy-saving is an eternal theme, while in the scenarios deployed multiple flows, the network resource competition directly influences the whole network performance. To address this issue, a cooperative routing scheme is developed by comprehensively taking both the routing selection and contention avoidance into account, in which, for the delay-tolerant sensing tasks, the concept of abstract domain is introduced to extend the coverage relay nodes, and the cooperative routings are carefully selected in terms of the specific sensing and transmission requirements. Simulation conducted on NS-2 platform demonstrates that the proposed cooperative routing outperforms the compared routing selection strategies in significantly balancing the energy distribution and prolonging the network lifetime.