Network convergence is regarded as the development tendency of the future wireless networks, for which self-organization paradigms provide a promising solution to alleviate the upgrading capital expenditures (CAPEX) and operating expenditures (OPEX). Self-optimization, as a critical functionality of self-organization, employs a decentralized paradigm to dynamically adapt the varying environmental circumstances while without relying on centralized control or human intervention. In this paper, we present comprehensive surveys of heterogeneous networks (HetNets) and investigate the enhanced self-optimization models. Self-optimization approaches such as dynamic mobile access network selection, spectrum resource allocation and power control for HetNets, etc., are surveyed and compared, with possible methodologies to achieve self-optimization summarized. We hope this survey paper can provide the insight and the roadmap for future research efforts in the self-optimization of convergence networks.

This paper considers a scenario that more D2D users exist in the cell, they compete for cellular resources to increase their own data rates, which may cause transmission interference to cellular users (CU) and the unfairness of resource allocation. We design a resource allocation scheme for selfish D2D users assisted by cooperative relay technique which is used to further enhance the users' transmission rates, meanwhile guarantee the QoS requirement of the CUs. Two transmission modes are considered for D2D users: direct transmission mode and cooperative relay transmission mode, both of which reuses the cellular uplink frequency resources. To ensure the fairness of resource distribution, Nash bargaining theory is used to determine the transmission mode and solve the bandwidth allocation problem for D2D users choosing cooperative relay transmission mode, and coalition formation game theory is used to solve the uplink frequency sharing problem between D2D users and CUs through a new defined "Selfish order". Through theoretical analysis, we obtain the closed Nash bargaining solution under CUs' rate constraints, and prove the stability of the formatted coalition. Simulation results show that the proposed resource allocation approach achieves better performance on resource allocation fairness, with only little sacrifice on the system sum rates.

This paper focuses on solving co-channel interference (CCI) issues arising in the open subscriber group (OSG) mode of heterogeneous networks (HetNets). Considering a general framework consisting of arbitrary number of picocells within a macro cell, where the inter-user interference (IUI) is the main CCI to macro user equipments (UEs), while the the inter-cell interference (ICI) is the major CCI to pico UEs. In this paper, three IA based transceiver design schemes are proposed. For macro cell, we uniformly use block diagonalization (BD) scheme to eliminate the IUI. And for picocells, three IA schemes are proposed to mitigate the ICI. The first scheme, named as zero forcing IA (ZF-IA) scheme, aligns the inter picocell interference onto an arbitrary sub-space of the cross-tier interference using ZF scheme. Considering the channel state information (CSI) of the desired channel of pico UEs, the second scheme, named as optimal desired sub-channel selected IA (ODC-IA) scheme, aligns the inter picocell interference onto a certain sub-space of the cross-tier interference, which guarantees the largest channel gain of the desired signal of pico UEs. The third IA scheme, named as maximum cross-tier interference selected IA (MI-IA) scheme, is designed for the system with less receive antennas. The inter picocell interference is aligned onto the space of the strongest cross-tier interference and only the interference on this space is nullified. The complexity analysis and simulations show that the proposed transceiver design schemes outperform the existing IA schemes in the OSG mode of HetNets, and the MI-IA scheme reduces the requirement of the receive antennas number with lower complexity.

Applications deployed in cloud receive a huge volume of requests from geographically distributed users whose satisfaction with the cloud service is directly proportional to the efficiency with which the requests are handled. Assignment of user requests based on appropriate load balancing principles significantly improves the performance of such cloud-based applications. To study the behavior of such systems, there is a need for simulation tools that will help the designer to set a test bed and evaluate the performance of the system by experimenting with different load balancing principles. In this paper, a novel architecture for cloud called Request Assignment Simulator (RAS) is proposed. It is a customizable, visual tool that simulates the request assignment process based on load balancing principles with a set of parameters that impact resource utilization. This simulator will help to ascertain the best possible resource allocation technique by facilitating the designer to apply and test different load balancing principles for a given scenario.

One of the major issues in emerging cloud management system needs the efficient service level agreement negotiation framework, with an optimal negotiation strategy. Most researchers focus mainly on the atomic service negotiation model, with the assistance of the Agent Controller in the broker part to reduce the total negotiation time, and communication overhead to some extent. This research focuses mainly on composite service negotiation, to further minimize both the total negotiation time and communication overhead through the pre-request optimization of broker strategy. The main objective of this research work is to introduce an Automated Dynamic Service Level Agreement Negotiation Framework (ADSLANF), which consists of an Intelligent Third-party Broker for composite service negotiation between the consumer and the service provider. A broker consists of an Intelligent Third-party Broker Agent, Agent Controller and Additional Agent Controller for managing and controlling its negotiation strategy. The Intelligent third-party broker agent manages the composite service by assigning its atomic services to multiple Agent Controllers. Using the Additional Agent Controllers, the Agent Controllers manage the concurrent negotiation with multiple service providers. In this process, the total negotiation time value is reduced partially. Further, the negotiation strategy is optimized in two stages, viz., Classified Similarity Matching (CSM) approach, and the Truncated Negotiation Group Gale Shapely Stable Matching (TNGGSSM) approach, to minimize the communication overhead.

Now a days, Efficient processing of Broadcast Queries is of critical importance with the ever-increasing deployment and use of mobile technologies. BQs have certain unique characteristics that the traditional spatial query processing in centralized databases does not address. In novel query processing technique, by maintaining high scalability and accuracy, latency is reduced considerably in answering BQs. Novel approach is based on peer-to-peer sharing, which enables us to process queries without delay at a mobile host by using query results cached in its neighboring mobile peers. We design and evaluate cooperative caching techniques to efficiently support data access in ad hoc networks. We first propose two schemes: Cache Data, which caches the data, and Cache Path, which caches the data path. After analyzing the performance of those two schemes, we propose a hybrid approach (Hybrid Cache), which can further improve the performance by taking advantage of Cache Data and Cache Path while avoiding their weaknesses. Cache replacement policies are also studied to further improve the performance. Simulation results show that the proposed schemes can significantly reduce the query delay and message complexity when compared to other caching schemes.

This paper presents a design for a throughput-efficient online relay selection scheme for dual-hop multi-relay cooperative networks. Problems arise with these networks due to unpredictability of the relaying link quality and high time-consumption to probe the dual-hop link. In this paper, we firstly propose a novel probing and relaying protocol, which greatly reduces the overhead of the dual-hop link estimation by leveraging the wireless broadcasting nature of the network. We then formulate an opportunistic relay selection process for the online decision-making, which uses a tradeoff between obtaining more link information to establish better cooperative relaying and minimizing the time cost for dual-hop link estimation to achieve higher throughput. Dynamic programming is used to construct the throughput-optimal control policy for a typically heterogeneous Rayleigh fading environment, and determines which relay to probe and when to transmit the data. Additionally, we extend the main results to mixed Rayleigh/Rician link scenarios, i.e., where one side of the relaying link experiences Rayleigh fading while the other has Rician distribution. Numerical results validate the effectiveness and superiority of our proposed relaying scheme, e.g., it achieves at least 107% throughput gain compared with the state of the art solution.

Tiered wireless sensor network is a network model of flexibility and robustness, which consists of the traditional resource-limited sensor nodes and the resource-abundant storage nodes. In such architecture, collected data from the sensor nodes are periodically submitted to the nearby storage nodes for archive purpose. When a query is requested, storage nodes also process the query and return qualified data as the result to the base station. The role of the storage nodes leads to an attack prone situation and leaves them more vulnerable in a hostile environment. If any of them is compromised, fake data may be injected into and/or qualified data may be discarded. And the base station would receive incorrect answers incurring malfunction to applications. In this paper, an efficient verifiable top-k query processing scheme called EVTQ is proposed, which is capable of verifying the authentication and completeness of the results. Collected data items with the embedded information of ordering and adjacent relationship through a hashed message authentication coding function, which serves as a validation code, are submitted from the sensor nodes to the storage nodes. Any injected or incomplete data in the returned result from a corresponded storage node is detected by the validation code at the base station. For saving communication cost, two optimized solutions that fuse and compress validation codes are presented. Experiments on communication cost show the proposed method is more efficiency than previous works.

This paper presents two distance geometry-based algorithms for wireless location in cellular network systems-distance geometry filtering (DGF) and distance geometry constraint (DGC). With time-of-arrival range measurements, the DGF algorithm estimates the mobile station position by selecting a set of measurements with relatively small NLOS (non-line-of-sight) errors, and the DGC algorithm optimizes the measurements first and then estimates the position using those optimized measurements. Simulation results show that the proposed algorithms can mitigate the impact of NLOS errors and effectively improve the accuracy of wireless location.

CISCO VNI predicted an average annual growth rate of 66% for mobile video traffic between 2014 and 2019 and accordingly much academic research related to video streaming has been initiated. In video streaming, Adaptive Bitrate (ABR) is a streaming technique in which a source video is stored on a server at variable encoding rates and each streaming user requests the most appropriate video encoding rate considering their channel capacity. However, these days, ABR related studies are only focusing on real-time rate adaptation omitting energy efficiency though it is one of the most important requirement for mobile devices, which may cause dissatisfaction for streaming users. In this paper, we propose an energy efficient prefetching based dynamic adaptive streaming technique by considering the limited characteristics of the batteries used in mobile devices, in order to reduce the energy waste and provide a similar level of service in terms of the average video rate compared to the latest ABR streaming technique which does not consider the energy consumption. The simulation results is showing that our proposed scheme saves 65~68% of energy at the average global mobile download speed compared to the latest high performance ABR algorithm while providing similar rate adaptation performance.

In many Radio Frequency Identification (RFID) applications, the reader recognizes the tags within its scope repeatedly. For these applications, some algorithms such as the adaptive query splitting algorithm (AQS) and the novel semi-blocking AQS (SBA) were proposed. In these algorithms, a staying tag retransmits its ID to the reader to be identified, even though the ID of the tag is stored in the reader's memory. When the length of tag ID is long, the reader consumes a long time to identify the staying tags. To overcome this deficiency, we propose a slot allocated blocking anti-collision algorithm (SABA). In SABA, the reader assigns a unique slot to each tag in its range by using a slot allocation mechanism. Based on the allocated slot, each staying tag only replies a short data to the reader in the identification process. As a result, the amount of data transmitted by the staying tags is reduced greatly and the identification rate of the reader is improved effectively. The identification rate and the data amount transmitted by tags of SABA are analyzed theoretically and verified by various simulations. The simulation and analysis results show that the performance of SABA is superior to the existing algorithms significantly.

This paper considers mobility control to improve packet delivery in delay-tolerant networks (DTNs) under group mobility. Based on the group structure in group mobility, we propose two mobility control techniques; group formation enforcement and group purposeful movement. Both techniques can be used to increase the contact opportunities between groups by extending the group's reachability. In addition, they can be easily integrated into some existing DTN routing schemes under group mobility to effectively expedite the packet delivery. This paper is divided into 2 parts. First, we study how our proposed mobility control schemes reduce the packet delivery delay in DTNs by integrating them into one simple routing scheme called group-epidemic routing (G-ER). For each scheme, we analytically derive the cumulative density function of the packet delivery delay to show how it can effectively reduce the packet delivery delay. Then, based on our second proposed technique, the group purposeful movement, we design a new DTN routing scheme, called purposeful movement assisted routing (PMAR), to further reduce the packet delay. Extensive simulations in NS2 have been conducted to show the significant improvement of PMAR over G-ER under different practical network conditions.

Peak to average power ratio (PAPR) is one of the main imperfections in the broadband communication systems with multiple carriers. In this paper, a new crest factor reduction (CFR) scheme based on interleaved phase sequence called Dummy Sequence Insertion Enhanced Partial Transmit Sequence (DSI-EPTS) is proposed which effectively reduces the PAPR while at the same time keeps the total complexity low. Moreover, the prototype of the proposed scheme in field programmable gate array (FPGA) is demonstrated. In DSI-EPTS scheme, a new matrix of phase sequence is defined which leads to a significant reduction in hardware complexity due to its less searching operation to extract the optimum phase sequence. The obtained results show comparable performance with slight difference due to the FPGA constraints. The results show 5 dB reduction in PAPR by applying the DSI-EPTS scheme with low complexity and low power consumption.

Since the variations of illumination, the irregular changes of human shapes, and the partial occlusions, multiple person tracking is a challenging work in computer vision. In this paper, we propose a graph clustering method based on spatio-temporal information of moving objects for multiple person tracking. First, the part-based model is utilized to localize individual foreground regions in each frame. Then, we heuristically leverage the spatio-temporal constraints to generate a set of reliable tracklets. Finally, the graph shift method is applied to handle tracklet association problem and consequently generate the completed trajectory for individual object. The extensive comparison experiments demonstrate the superiority of the proposed method.

Multiple projectors with partially overlapping regions can be used to project a seamless image on a large projection surface. With the advent of high-resolution photography, such systems are gaining popularity. Experts set up such projection systems by subjectively identifying the types of errors induced by the system in the projected images and rectifying them by optimizing (correcting) the parameters associated with the system. This requires substantial time and effort, thus making it difficult to set up such systems. Moreover, comparing the performance of different multi-projector display (MPD) systems becomes difficult because of the subjective nature of evaluation. In this work, we present a framework to quantitatively determine the quality of an MPD system and any image projected using such a system. We have divided the quality assessment into geometric and photometric qualities. For geometric quality assessment, we use Feature Similarity Index (FSIM) and distance-based Scale Invariant Feature Transform (SIFT). For photometric quality assessment, we propose to use a measure incorporating Spectral Angle Mapper (SAM), Intensity Magnitude Ratio (IMR) and Perceptual Color Difference (ΔE). We have tested the proposed framework and demonstrated that it provides an acceptable method for both quantitative evaluation of MPD systems and estimation of the perceptual quality of any image projected by them.

More than 1 billion mobile apps (smartphone applications) have been released worldwide. Competition among developers of apps that are available in app stores has intensified because of increasing demand. App icons with an appealing design can instantly increase attention. Miryoku Engineering methods were used and combined with the Kansei interface model to examine the relationship between attractive icons and users. The evaluation grid method (EGM) is a qualitative method that was used to evaluate the icons, and Quantification Theory Type I is a quantitative method that was used to analyze the influence of design elements in icons. Eight attractive factors of app icons were determined using EGM, and six specific factors were identified using questionnaires. The quantitative results indicated that user cognition and emotion were influenced by the various design elements. The impact on the attractive factors of a single design element differed among users with diverse backgrounds. App icons were assessed on the basis of aesthetics to identify attractive factors and thereby assist designers in understanding and implementing design elements and improving the overall visual appeal of their apps. The result of this investigation is crucial to the presentation of app icons in online app stores.

The emerging high efficiency video coding (HEVC) standard adopts the quadtree-structured transform unit (TU) in the residual quadtree (RQT) coding. Each TU allows to be split into four equal sub-TUs recursively. The RQT coding is performed for all the possible transform depth levels to achieve the highest coding efficiency, but it requires a very high computational complexity for HEVC encoders. In order to reduce the computational complexity requested by the RQT coding, in this paper, we propose a fast TU size decision method incorporating an adaptive maximum transform depth determination (AMTD) algorithm and a full check skipping - early termination (FCS-ET) algorithm. Because the optimal transform depth level is highly content-dependent, it is not necessary to perform the RQT coding at all transform depth levels. By the AMTD algorithm, the maximum transform depth level is determined for current treeblock to skip those transform depth levels rarely used by its spatially adjacent treeblocks. Additionally, the FCS-ET algorithm is introduced to exploit the correlations of transform depth level between four sub-CUs generated by one coding unit (CU) quadtree partitioning. Experimental results demonstrate that the proposed overall algorithm significantly reduces on average 21% computational complexity while maintaining almost the same rate distortion (RD) performance as the HEVC test model reference software, HM 13.0.

Mobile devices are becoming powerful enough to realize augmented reality (AR) application. This paper introduces two AR methods to estimate an environmental illumination distribution of a scene. In the first method, we extract the lighting direction and intensity from input images captured with a front-side camera of a mobile device, using its orientation sensor. The second method extracts shadow regions cast by three dimensional (3D) AR marker of known shape and size. Because previous methods examine per pixel shadow intensity, their performances are much affected by the number of sampling points, positions, and threshold values. By using a simple binary operation between the previously clustered shadow regions and the threshold real shadow regions, we can compute efficiently their relative area proportions according to threshold values. This area-based method can overcome point sampling problem and threshold value selection. Experiment results demonstrate that the proposed methods generate natural image with multiple smooth shadows in real-time.

We propose an efficient method of extracting targets within a region of interest in non-homogeneous infrared images by using a principal component analysis (PCA) plane and adaptive Gaussian kernel. Existing approaches for extracting targets have been limited to using only the intensity values of the pixels in a target region. However, it is difficult to extract the target regions effectively because the intensity values of the target region are mixed with the background intensity values. To overcome this problem, we propose a novel PCA based approach consisting of three steps. In the first step, we apply a PCA technique minimizing the total least-square errors of an IR image. In the second step, we generate a binary image that consists of pixels with higher values than the plane, and then calculate the second derivative of the sum of the square errors (SDSSE). In the final step, an iteration is performed until the convergence criteria is met, including the SDSSE, angle and labeling value. Therefore, a Gaussian kernel is weighted in addition to the PCA plane with the non-removed data from the previous step. Experimental results show that the proposed method achieves better segmentation performance than the existing method.

Cryptography provides an effective solution to secure the communication over public networks. The communication over public networks that includes electronic commerce, business and military services, necessitates the requirement of simple and robust encryption techniques. In this paper, a novel image encryption method which employs calligraphy based hybrid scan and random number is presented. The original image is scrambled by pixel position permutation with calligraphy based diagonal and novel calligraphy based scan patterns. The cipher image is obtained by XORing the scrambled image with random numbers. The suggested method resists statistical, differential, entropy, and noise attacks which have been demonstrated with a set of standard images.