Energy-efficient mechanism based on ACO for the coverage problem in sensor networks

An energy-efficient heuristic mechanism is presented to obtain the optimal solution for the coverage problem in sensor networks. The mechanism can ensure that all targets are fully covered corresponding to their levels of importance at minimum cost, and the ant colony optimization algorithm （ACO） is adopted to achieve the above metrics. Based on the novel design of heuristic factors, artificial ants can adaptively detect the energy status and coverage ability of sensor networks via local information. By introducing the evaluation function to global pheromone updating rule, the pheromone trail on the best solution is greatly enhanced, so that the convergence process of the algorithm is speed up. Finally, the optimal solution with a higher coverage- efficiency and a longer lifetime is obtained.

Maximum-Profit Advertising Strategy Using Crowdsensing Trajectory Data

Out-door billboard advertising plays an important role in attracting potential customers.However,whether a customer can be attracted is influenced by many factors,such as the probability that he/she sees the billboard,the degree of his/her interest,and the detour distance for buying the product.Taking the above factors into account,we propose advertising strategies for selecting an effective set of billboards under the advertising budget to maximize commercial profit.By using the data collected by Mobile Crowdsensing(MCS),we extract potential customers’implicit information,such as their trajectories and preferences.We then study the billboard selection problem under two situations,where the advertiser may have only one or multiple products.When only one kind of product needs advertising,the billboard selection problem is formulated as the probabilistic set coverage problem.We propose two heuristic advertising strategies to greedily select advertising billboards,which achieves the expected maximum commercial profit with the lowest cost.When the advertiser has multiple products,we formulate the problem as searching for an optimal solution and adopt the simulated annealing algorithm to search for global optimum instead of local optimum.Extensive experiments based on three real-world data sets verify that our proposed advertising strategies can achieve the superior commercial profit compared with the state-of-the-art strategies.

Multilevel coverage location model of earthquake relief material storage repository considering distribution time sequence characteristics

The scientific location of earthquake emergency supply warehouses is conducive to the effective distribution of emergency relief resources and improved rescue efficiency in earthquake hazard. Comprehensively considering the regional population as well as coverage quality at the demand points, this paper aims to divide the coverage thresholds of earthquake emergency rescue and logistic supplies according to their time-series features,and to build a location model for supply warehouses according to the variety and amount of stored supplies considering their time-series features, in hope of optimizing the set covering issue of earthquake relief supply warehouses. The solution is approached with two methods: the target deviation rate minimization model and NSGA-Ⅱ algorithm. The results obtained by solving the target deviation rate minimization model can balance every target. The branch and bound algorithm can find the global optimal solution at a certain calculation scale with high calculation efficiency, but its efficiency decreases significantly when the operation scale increases. The NSGA-Ⅱ algorithm is more suitable for large-scale solution calculations with high calculation efficiency, and it can output a set of non-inferior solutions for decision makers to select from according to different preference. Taking Aba Prefecture in Sichuan Province as illustration, the feasibility of the model is validated;meanwhile, the effectiveness and benefits of the two approaches in solving the problem of multi-objective set covering of the warehouses are compared and analyzed.