In the Long Term Evolution(LTE)downlink multicast scheduling,Base Station(BS)usually allocates transmit power equally among all Resource Blocks(RBs),it may cause the waste of transmit *** avoid it,this paper put forwa...
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In the Long Term Evolution(LTE)downlink multicast scheduling,Base Station(BS)usually allocates transmit power equally among all Resource Blocks(RBs),it may cause the waste of transmit *** avoid it,this paper put forward a new algorithm for LTE multicast downlink scheduling called the Energy-saving based Inter-group Proportional Fair(EIPF).The basic idea of EIPF is to calculate an appropriate transmitting power for each group according to its data rate respectively,and then follow the inter-group proportional fair principle to allocate RBs among multicast *** results of EIPF simulation show that the proposed algorithm not only can reduce the transmit power of BS effectively but also improve the utilization rate of energy.
In Internet of vehicles, vehicular edge computing(VEC) as a new paradigm can effectively accomplish various tasks. Due to limited computing resources of the roadside units(RSUs), computing ability of vehicles can be a...
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In Internet of vehicles, vehicular edge computing(VEC) as a new paradigm can effectively accomplish various tasks. Due to limited computing resources of the roadside units(RSUs), computing ability of vehicles can be a powerful supplement to computing resources. Then the task to be processed in data center can be offloaded to the vehicles by the RSUs. Due to mobility of the vehicles, the tasks will be migrated among the RSUs. How to effectively offload multiple tasks to the vehicles for processing is a challenging problem. A mobility-aware multi-task migration and offloading scheme for Internet of vehicles is presented and analyzed. Considering the coupling between migration and offloading, the joint migration and offloading optimization problem is formulated. The problem is a NP-hard problem and it is very hard to be solved by the conventional methods. To tackle the difficult problem, the idea of alternating optimization and divide and conquer is introduced. The problem can be decoupled into two sub-problems: computing resource allocation problem and vehicle node selection problem. If the vehicle node selection is given, the problem can be solved based on Lagrange function. And if the allocation of computing resource is given, the problem turns into a 0-1 integer programming problem, and the linear relaxation of branch bound algorithm is introduced to solve it. Then the optimization value is obtained through continuous iteration. Simulation results show that the proposed algorithm can effectively improve system performance.
In order to solve the controllability problem of worm attack range and effect in network counterwork and achieve the precise attack on the target host, we propose a propagation control method based on lifetime and a d...
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wireless Multimedia sensornetwork (WMSN) need to transfer large amounts of video streaming data, how to achieve efficient and reliable transmission becomes a research hotspot. Layered scalable coding techniques can r...
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For some existing handoff control algorithms in Aerospace Information network, the success rate of their handoff calls is not high. This paper proposes a handoff control algorithm based on service priorities and chann...
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A secure communication mechanism is necessary in the applications of wireless Multimedia sensornetworks (WMSNs), which is more vulnerable to security attacks due to the presence of multimedia data. Additionally, give...
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A secure communication mechanism is necessary in the applications of wireless Multimedia sensornetworks (WMSNs), which is more vulnerable to security attacks due to the presence of multimedia data. Additionally, given the limited technological resources (in term of energy, computation, bandwidth, and storage) of sensor nodes, security and privacy policies have to be combined with energy-aware algorithms and distributed processing of multimedia contents in WMSNs. To solve these problems in this paper, an energy efficient distributed steganography scheme, which combines steganography technique with the concept of distributed computing, is proposed for secure communication in WMSNs. The simulation results show that the proposed method can achieve considerable energy efficiency while assuring the communication security simultaneously.
With the rapid development of e-commerce, the security issues of collaborative filtering recommender systems have been widely investigated. Malicious users can benefit from injecting a great quantities of fake profile...
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With the rapid development of e-commerce, the security issues of collaborative filtering recommender systems have been widely investigated. Malicious users can benefit from injecting a great quantities of fake profiles into recommender systems to manipulate recommendation results. As one of the most important attack methods in recommender systems, the shilling attack has been paid considerable attention, especially to its model and the way to detect it. Among them, the loose version of Group Shilling Attack Generation Algorithm (GSAGenl) has outstanding performance. It can be immune to some PCC (Pearson Correlation Coefficient)-based detectors due to the nature of anti-Pearson correlation. In order to overcome the vulnerabilities caused by GSAGenl, a gravitation-based detection model (GBDM) is presented, integrated with a sophisticated gravitational detector and a decider. And meanwhile two new basic attributes and a particle filter algorithm are used for tracking prediction. And then, whether an attack occurs can be judged according to the law of universal gravitation in decision-making. The detection performances of GBDM, HHT-SVM, UnRAP, AP-UnRAP Semi-SAD,SVM-TIA and PCA-P are compared and evaluated. And simulation results show the effectiveness and availability of GBDM.
Wi-Fi has been widely deployed with the rapid development of wirelesscommunication technique. Wi-Fi hotspots are popular in campus, making convenient wirelessnetwork access possible. However, during class teaching, ...
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Low earth orbit(LEO) satellite network is an important development trend for future mobile communication systems, which can truly realize the“ubiquitous connection” of the whole world. In this paper, we present a co...
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Low earth orbit(LEO) satellite network is an important development trend for future mobile communication systems, which can truly realize the“ubiquitous connection” of the whole world. In this paper, we present a cooperative computation offloading in the LEO satellite network with a three-tier computation architecture by leveraging the vertical cooperation among ground users, LEO satellites, and the cloud server, and the horizontal cooperation between LEO satellites. To improve the quality of service for ground users, we optimize the computation offloading decisions to minimize the total execution delay for ground users subject to the limited battery capacity of ground users and the computation capability of each LEO satellite. However, the formulated problem is a large-scale nonlinear integer programming problem as the number of ground users and LEO satellites increases, which is difficult to solve with general optimization algorithms. To address this challenging problem, we propose a distributed deep learning-based cooperative computation offloading(DDLCCO) algorithm, where multiple parallel deep neural networks(DNNs) are adopted to learn the computation offloading strategy dynamically. Simulation results show that the proposed algorithm can achieve near-optimal performance with low computational complexity compared with other computation offloading strategies.
In this paper, we revisit the problem of target detection in wirelesssensornetworks (WSNs). Because that the practical environment of WSNs is very complex, and usually the target signal is mixed with a lot of random...
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