- EI核心期刊
A survey on caching techniques of the content centric networking (CCN) represented information centric networking (ICN) was given, which categorize the main research idea and methodology. Firstly, the operating principle of ICN caching as well as its key research topics was outlined and the advantage of the ICN using in the wireless networks was analyzed. The research on CCN represented ICN caching deployment scheme design and theory modeling analysis was summarized respectively. Finally, the developments and challenges of ICN caching techniques in the future research was given. The possible research aspects along with the key problems was found, which can provide a useful reference for further study of ICN caching.
In response to the sensitive information leakage problem of Android applications, a detection scheme based on fine-grained information flow tracking strategies and static taint tracking technology was proposed. According to the syntax and semantic of Smali code, the internal call graph of application, the Android communication mechanism, and the fine-grained taint track rules were constructed, the taint analysis was executed as well on the application according to the different leak manner and the propagation strategies. The sensitive information leakage was determined by the taint analysis result. Experiments show that the scheme can detect a variety of ways of sensitive data leakage effectively, improve the detection accuracy and flexibility, and reduce the uncomprehensive of information flow path and false positive rate in the process of detection.
For multi-frequency channel interference alignment(IA) system with single data stream transmitting for each user,the user solutions of capacities are important. However, there exist methods which can obtain optimal IA solution. Considering the complex multimodal characteristics of solution space of multi-frequency channel in LA system, a new gradient-exploited particle swarm optimization algorithm was proposed to search for the global optimal solution which directly takes the network sum rate as its objective function. The capability for searching the optimal solution is enhanced by projecting the velocity vector on the normal plane of the position vector; the convergence rate is speeded through learning along the gradient of the network sum rate function. Numerical simulation shows that, the proposed method will obtain a better network sum rate performance than that of the existing algorithms.
The frequency response masking (FRM) technology is widely used in digital channelized and related fields because of advantages of the filter design with narrow transition band. An improved structure of even arrangement channelized based on FRM was proposed according to the problem of high complexity brought by design of narrow transition band channelized. The prototype filter of the improved structure was designed by half-band filter, and also two masking filters are designed by the same low pass filter through modulation. The sub-band signals of each channel are synthesized as the output signal with upper and lower arms. The improved structure is derived from the condition of non-maximally decimated based on FRM, and the computational complexity of the structure is less than the conventional structure. The improved channelized structure has the extensive applicability without the limit of higher sampling rate due to the decimation module placed at the forefront of channelized. Simulations show that the improved structure is correct and can save 67.9% multipliers compared with polyphase structure under the conditions of 16-channels example.
Bipartite-graph based probabilistic spreading (ProbS) algorithms often focus on optimizing the accuracy of recommendation lists while ignoring diversity, another key property to evaluate the quality of recommendation results. In order to deal with this problem, an improved probabilistic spreading (iProbS) algorithm is proposed in the present paper. The iProbS algorithm divides the recommendation process into three steps of resource spreading, and each resource spreading step constrained by spreading probability and spreading cost simultaneously. Users' scores rating on items are applied to compute spreading probability, at the same time, the degree of items, entropy of users, and the neighbors of items are considered for computing spreading costs. Extensive experiments on two widely used data sets (from MovieLens and Netflix) show that iProbS can effectively improve recommending accuracy, aggregate diversity, individual diversity, and sales balance of recommendation lists. Finally, computational complexities of iProbS are studied from its different computing steps.
Aiming at the high energy consumption of mobile terminal under cellular networks, a new energy optimization algorithm balance optimization algorithm (BOA) based on time series is proposed to improve the energy efficiency of smartphones. The proposed algorithm builds the auto-regressive and moving average model for the data blocks in the cellular network, and dynamically adjusts the tail time to achieve the purpose of reducing the energy consumption by predicting the arrival time of the next block. Experiments show that BOA can achieve the average model matching rate up to 93.86%. Compared to traditional fixed-tail algorithm, the BOA enables reduce energy consumption by 42.25%,and analysis shows that the longer smartphones are used, the higher energy efficiency can be achieved.
Many proposals about the optimization of cache management policies depend on set dueling, and they choose policies according to the results of miss rates. However, they are facing challenges in multicore since they have lower accuracy and higher storage overhead. The main reason is that they only consider the results of cache replacement policies rather than the characteristic of cache access sequences (or access pattern). Therefore, an online access pattern identification method, complex stack distance weighting method was proposed, and an adaptive cache replacement policy, least recently used-C (LRU-C), was put forward. Its basic idea is to adjust the insertion position according to the result of the online access pattern identification. Experiment in the full-system Simics running 18 benchmarks from SPEC CPU2000/2006 shows that the performance of LRU-C is better than those of dynamic insertion policy,re-reference interval prediction,thread aware dynamic insertion policy and promotion/insertion pseudo-partitioning.
The research on the character segmentation of the horizontal caption line in news images was made in this article. In order to overcome the character splitting problem caused by existing single character based segmentation methods, a response function was proposed based on character distribution. The character segmentation problem is converted into an optimal problem, and the character segmentation can be attained by turning to the optimal result. The algorithm mainly contains two parts:First, the rough width of a single character is determined based on the vertical projection histogram, which is utilized to construct a variable length template; Then, the template response function is constructed and the left/right boundary position of a single character is determined by the optimal value of the response function of different length templates; Last, output the segmentation results. Experimental results show that the proposed method can obtain satisfactory results for adhesion/non-adhesion character images.
The flow table updating with loop-free consistence is one of the most important issues in software defined networking (SDN), in which, the optimal scheme has high computing complexity, while the single/double directional updating schemes have low computing complexity, however, the length of dependency chain is difficult to be optimized. The article presents a consistent flow update scheme based on multi-directional searching. The scheme was proved loop-free consistent. Simulation shows that the scheme shortens the length of dependency chain, closes to the optimal scheme and effectively reduces the working load on controller.
A mutual authentication protocol was proposed for large-scale radio frequency identification (RFID) system. Taking advantage of pseudo random number generator with little calculation resource requirement, the proposed protocol is suitable for low-cost tag environment with small storage space and low compute power. The slope calculation method of a line was adopted to realize both sides of authentication share a pair of keys and time complexity required to identify a tag can be reduced to O(1). The timestamp was introduced to resist replay attacks, and updates the identity to prevent location tracking. Formal proof shows that it realizes mutual authentication between the reader and the tag. Simulation shows that the proposed protocol can save 9% authentication time compared with some similar existing mainstream protocols.
To solve the problem that the load which is carried by gateway node and that the network links in wireless Mesh network is imbalanced, a resource allocation model was constructed to optimize network weighted throughput by selecting the best gateway node and designing the weight on each link. A joint power control and channel assignment algorithm (QDJPCA) was proposed based on Q learning and differential evolution under the resource allocation model. In this algorithm, the channel assignment is achieved by obtaining the feedback results of power control, using the multiple mutations and adaptive crossover rate based differential evolution algorithm. In each iteration, to achieve power control, the Q learning algorithm based on state clustering and state correction is utilized on the channel assignment result. NS-3 simulation shows that the QDJPCA can not only effectively solve the proposed resource allocation model, but also improve the overall network performance through preferentially ensuring the gateway load balancing and throughput performance of heavy load link.
In order to group three-dimensional data, the thought of fuzzy co-clustering was adopted, and an information bottleneck based fuzzy tri-clustering algorithm, named IBFTC, was presented. The IBFTC specifies membership function for each dimension, simultaneously generates fuzzy clusters on three dimensions and adds information bottleneck theory into objective function for measuring distances between objects and clusters. Experiments on the MovieLens dataset evaluate the performances of IBFTC from several aspects. Experiment shows that IBFTC could achieve higher accuracy than conventional fuzzy co-clustering algorithms.
An algorithm of randomly intensive dissemination of video fragments in opportunistic network was proposed to satisfy the requirement of more number of video segments distributed randomly in time axis and sequenced in content so that users can acquire effective information of the original video. The proposed algorithm can guide transportation of video blocks while delivery delay is reduced sharply. Simulations show that random-sequential content spreading (RSCS) significantly outperforms these approaches in terms of random-sequential index. Moreover, RSCS also achieves better performance levels in ratio of delivery and latency than sequential solution.
In wireless sensor network (WSN), the centralized learning method by transmitting all training samples scattered across different sensor nodes to a centralized data center to train classifier will significantly increase the communication cost. To decrease the communication cost in transmitting training samples, a distributed learning method for kernel minimum squared error (KMSE) by incorporating L1 regularized term was studied, which just relies on in-network processing between single-hop neighboring nodes. Each node obtains its local optimum sparse model by constructing the optimization problem of L1 regularized KMSE based on its local training samples and solving it using parallel projections and alternating the direction method of multipliers, then a consistent model is achieved on all nodes by using the global average consensus algorithm. For carrying out this method,a new distributed training algorithm for L1-regularized kernel minimum squared error based on parallel projections (L1-DKMSE-PP) was proposed. Simulations show that L1-DKMSE-PP can obtain almost the same prediction accuracy as that of the centralized counterpart and a sparser model, and more importantly, it can significantly reduce the communication cost.
In flow-based passive measurement of the Internet, the measurement of flow size and flow volume is a basic requirement. To resolve the contradiction of increasing network link speed and small-sized fast memory chipset, a non-linear sampling algorithm which is named discrete counting (DISCO), was proposed in related research work. In order to meet the need of wire-speed network traffic measurement, DISCO is suggested to be implemented by hardware approaches, such as field-programmable gate array (FPGA). However, DISCO involves complex calculations with high precision, which give rise to a series of challenges in hardware acceleration. To solve the problems, a hardware-friendly refined algorithm was designed, which employs multiple lookup tables and a normalization method. Simulation was conducted to verify the validity of the refined algorithm. An FPGA-based prototype was made. Experiments show that the refined algorithm can achieve wire-speed flow measurement of a 40 Gbit/s link, with small hardware logic resources consumption of FPGA. The average relative error and maximum relative error of the refined DISCO algorithm are close to the original one.
In order to solve the problem of high cost of network construction and low lifetime of network, it is a problem to solve the problem of high cost of network construction and low network lifetime of relay nodes in wireless sensor network,this article proposed a new relay node placement algorithm based on the greedy criterion. By adopting the performance evaluation criteria of the balanced energy consumption rate and the total energy consumption of the network, the algorithm contrasts the recent greedy criterion, the directional greedy criterion and the minimum angle of greedy criterion respectively, and then constrains and optimizes the data transmission path of node by introducing data flow restriction, communication capacity and maximum data transfer times. Experiments show that, the recent greedy criterion has less energy consumption, and can balance the energy consumption of each node in the network. Moreover, this recent greedy criterion can not only give proper location of each node, but also reduce the energy consumption of the whole network effectively.
To improve the accuracy and efficiency of existing fault injection tools, a C-language oriented fault injection and execution platform was presented. The platform is constructed by fault injection, fault model, batch execution and results analysis modules. Experiments show that comparing with other fault injection tool when used the open source projects, the platform can support more practical engineering functions.
A packet reordering-controlled load distribution model for real-time multipath transport was proposed. According to the feedback information of path transmission quality of all paths and packet out-of-ordering between paths from the destination, the source updated dynamically the load share of paths. Packet out-of-ordering risk was minimized while the load balancing proportional to the path transmission quality was satisfied. Simulations show that the proposed model can effectively reduce the total packet loss rate of the destination caused by packet out-of-ordering.
In order to effectively control the security risks of the business process in the information system, a risk control method based on work-flow (WRCM) was proposed. It includes two operations, the risk quantification and the risk control. In the risk quantification operation, the risk quantification parameters are defined and initialized. In the risk control operation, the minimum residual risk damage was used as object function to get a minimum risk damage deployment scheme based on linear programming method through the control effect maximization operation. Then, the minimum control cost was used as object function to get the minimum control cost deployment scheme through the control cost minimization operation. Experiments show that the WRCM has preferable risk control effect and lower control cost.
The energy efficient and real-time data collecting problem in wireless sensor network was studied. The mobile data collecting protocol consists four phases:nodes clustering, routes planning, routes combine and data collecting is proposed. Two heuristic algorithms save and nearest neighbor were presented to build data collecting routes which incur the least mobile cost while satisfy the deadline constraint. Simulations show that the proposed heuristic routes planning algorithms have good performance in terms of energy saving, deadline guarantee and travel cost reduction.
The energy efficient and real-time data collecting problem in wireless sensor network was studied. The mobile data collecting protocol consists four phases:nodes clustering, routes planning, routes combine and data collecting is proposed. Two heuristic algorithms save and nearest neighbor were presented to build data collecting routes which incur the least mobile cost while satisfy the deadline constraint. Simulations show that the proposed heuristic routes planning algorithms have good performance in terms of energy saving, deadline guarantee and travel cost reduction.
The mobile relay selection problems in multi-hop cellular network are studied. The selection of mobile relay affects such performances as the throughput of the system, spectral efficiency and relay switching probability. In order to improve the throughput and reduce the relay switching probability, the mobile state of the users and the relay nodes in the dynamic scenario was analyzed, then a multi-objective joint optimization based mobile relay selection scheme was proposed. The scheme analyzes two factors which affect the system throughput and the relay switching probability in dynamic scenario. The mobile characteristic of multi-hop cellular network and the state of users' call arrival are taken into full consideration. Simulation shows that the algorithm can improve the users' throughput effectively and reduce the relay switching probability.
Crosstalk is one of the bottlenecks in high-speed circuits for rate and density continuing increasing. Aiming at the problem of crosstalk between multiple transmission lines, a crosstalk cancellation method of three coupled microstrip lines based on eigen value decomposition of coupled transmission lines-channel transmission matrix was proposed. The circuit implementation structure of the method was studied and the circuit parameters were provided. Simulations show that crosstalk can be mostly eliminated and the quality of eye diagram can be improved obviously.
The piezoelectric and electromagnetic energy harvesting technology for vehicle sensors self-powered was studied. The mathematical models for the composite energy collection system was put forword, and the relationship about the resonance frequency of the system was analyzed with regard to the system configuration parameters. A piezoelectric and electromagnetic energy harvesting device was designed. Experiment shows it has good agreement with the analytical results in trend. The maximum of load power of the composite harvester achieves 3.75 mW at the resonant frequency of 18 Hz with acceleration of 0.5 g, and is increased by 17% compared with 3.2 mW of the single electromagnetic technique.
In actual network confrontations, attack and defense is, in fact, combined in one body, i.e., each person is not only the attacking side (hackers), but also the defending side(the Honker). In addition to the most common "1 to 1" and "one to many" attack-and-defense, there are also the 2-group cases, i.e., the persons are divided into two groups (for example, the historical NATO and the Warsaw Pact) such that one group attacks and defenses the other group. Of course, the more general cases are the "all parties attack-and-defense", i.e., all persons attack and defense each other. In this paper, the reachable limitations of all "dictatorship evaluate" events are listed for all of these possible confrontations, under the assumption of "any person not deceive ourselves".