Cloud computing evolve as a cost effective business model for IT companies to focus on their core business without perturbing on infrastructure related issues. Hence, major IT firms and Small & Medium Enterprises (SME) are adopting cloud services on rental basis from cloud providers. Cloud Service level agreements (SLA) act as a key liaison between consumers and providers on renting Anything as a Service (AaaS). Design of such an agreement must aim for greater profit to providers as well as assured availability of services to consumers. However in reality, cloud SLA is not satisfying the parties involved because of its inherent complex nature and issues. Also currently most of the agreements are unilateral to favour the provider. This study focuses on comprehensive, 360-degree survey on different aspects of the cloud service agreements. We detailed the life cycle of SLA based on negotiation, different types of SLA, current standards, languages & characteristics, metrics and issues involved in it. This study will help the cloud actors to understand and evaluate the agreements and to make firm decision on negotiation. The need for standardized, bilateral, semantic SLA has also been proposed.

The rapid increase of smart mobile devices and mobile applications has led to explosive growth of data traffic in cellular network. Offloading data traffic becomes one of the most urgent technical problems. Recent work has proposed to exploit opportunistic communications to offload cellular traffic for mobile data dissemination services, especially for accepting large delayed data. The basic idea is to deliver the data to only part of subscribers (called target-nodes) via the cellular network, and allow target-nodes to disseminate the data through opportunistic communications. Human mobility shows temporal and spatial characteristics and predictability, which can be used as effective guidance efficient opportunistic communication. Therefore, based on the regularity of human mobility we propose NodeRank algorithm which uses the encounter characteristics between nodes to choose target nodes. Different from the existing work which only using encounter frequency, NodeRank algorithm combined the contact time and inter-contact time meanwhile to ensure integrity and availability of message delivery. The simulation results based on real-world mobility traces show the performance advantages of NodeRank in offloading efficiency and network redundant copies.

Small cells are deployed in Heterogeneous Networks (HetNet) to improve overall performance. These access points can provide high-rate mobile services at hotspots to users. In a Small Cell Network (SCN), the good deployment of small cells can guarantee the performance of users on the basis of average and cell edge spectrum efficiency. In this paper, the performance of small cell deployment is analyzed by using system-level simulations. The positions of small cells can be adjusted according to the deployment radius and angle. Moreover, different Inter-Cell Interference Coordination (ICIC) techniques are also studied, which can be implemented either in time domain or in frequency domain. The network performances are evaluated under different ICIC techniques when the locations of Small evolved Nodes (SeNBs) vary. Simulation results show that the average throughput and cell edge throughput can be greatly improved when small cells are properly deployed with the certain deployment radius and angle. Meanwhile, how to optimally configure the parameters to achieve the potential of the deployment is discussed when applying different ICIC techniques.

Wireless Sensor Networks (WSNs) are widely used in geographically isolated applications like military border area monitoring, battle field surveillance, forest fire detection systems, etc. Uninterrupted power supply is not possible in isolated locations and hence sensor nodes live on their own battery power. Localization of sensor nodes in isolated locations is important to identify the location of event for further actions. Existing localization algorithms consume more energy at sensor nodes for computation and communication thereby reduce the lifetime of entire WSNs. Existing approaches also suffer with less localization coverage and localization accuracy. The objective of the proposed work is to increase the lifetime of WSNs while increasing the localization coverage and localization accuracy. A novel intelligent unmanned aerial vehicle anchor node (IUAN) is proposed to reduce the communication cost at sensor nodes during localization. Further, the localization computation cost is reduced at each sensor node by the proposed intelligent arc selection (IAS) algorithm. IUANs construct the location-distance messages (LDMs) for sensor nodes deployed in isolated locations and reach the Control Station (CS). Further, the CS aggregates the LDMs from different IUANs and computes the position of sensor nodes using IAS algorithm. The life time of WSN is analyzed in this paper to prove the efficiency of the proposed localization approach. The proposed localization approach considerably extends the lifetime of WSNs, localization coverage and localization accuracy in isolated environments.

In this paper, we investigate the multi-resource allocation problem, a unique feature of which is that the multiple resources can compensate each other while achieving the desired system performance. In particular, power and time allocations are jointly optimized with the target of energy efficiency under the resource-limited constraints. Different from previous studies on the power-time tradeoff, we consider a multi-server case where the concurrent serving users are quantitatively restricted. Therefore user selection is investigated accompanying the resource allocation, making the power-time tradeoff occur not only between the users in the same server but also in different servers. The complex multivariate optimization problem can be modeled as a variant of 2-Dimension Bin Packing Problem (V2D-BPP), which is a joint non-linear and integer programming problem. Though we use state decomposition model to transform it into a convex optimization problem, the variables are still coupled. Therefore, we propose an Iterative Dual Optimization (IDO) algorithm to obtain its optimal solution. Simulations show that the joint multi-resource allocation algorithm outperforms two existing non-joint algorithms from the perspective of energy efficiency.

In dual-channel networks (DCNs), all frequency hopping (FH) sequences used for data channels are chosen from the original FH sequence used for the control channel by shifting different initial phases. As the number of data channels increases, the hitting frequency point problem becomes considerably serious because DCNs is non-orthogonal synchronization network and FH sequences are non-orthogonal. The increasing severity of the hitting frequency point problem consequently reduces the resource utilization efficiency. To solve this problem, we propose a novel hitting frequency point collision avoidance method, which consists of a sequence-selection strategy called sliding correlation (SC) and a collision avoidance strategy called keeping silent on hitting frequency point (KSHF). SC is used to find the optimal phase-shifted FH sequence with the minimum number of hitting frequency points for a new data channel. The hitting frequency points and their locations in this optimal sequence are also derived for KSHF according to SC strategy. In KSHF, the transceivers transmit or receive symbol information not on the hitting frequency point, but on the next frequency point during the next FH period. Analytical and simulation results demonstrate that unlike the traditional method, the proposed method can effectively reduce the number of hitting frequency points and improve the efficiency of the code resource utilization.

In this paper, we study the design of network coding for the generalized transmit scheme in multiple input multiple output Y channel, where K users wish to exchange specified and shared information with each other within two slots. Signal space alignment at each user and the relay is carefully constructed to ensure that the signals from the same user pair are grouped together. The cross-pair interference can be canceled during both multiple accessing channel phase and broadcasting channel phase. The proposed signal processing scheme achieves the degrees of freedom of ${\eta}(K)=K^2$ with fewer user antennas.

With the development of cloud computing, more and more Web services are deployed on geo-distributed datacenters and are offered to cloud users all over the world. Through service composition technologies, these independent fine-grain services can be integrated to value-added coarse-grain services. During the composition, a number of Web services may provide the same function but differ in performance. In addition, the distribution of cloud datacenters presents a geographically dispersive manner, which elevates the impact of the network on the QoS of composite services. So it is important to select an optimal composition path in terms of QoS when many functionally equivalent services are available. To achieve this objective, we first present a graph model that takes both QoS of Web services and QoS of network into consideration. Then, a novel approach aiming at selecting the optimal composition path that fulfills the user's end-to-end QoS requirements is provided. We evaluate our approach through simulation and compare our method with existing solutions. Results show that our approach significantly outperforms existing solutions in terms of optimality and scalability.

Deploying sensors into a target region is a key issue to be solved in building a wireless sensor network. Various deployment algorithms have been proposed by the researchers, and most of them are evaluated under the ideal conditions. Therefore, they cannot reflect the real environment encountered during the deployment. Moreover, it is almost impossible to evaluate an algorithm through practical deployment. Because the deployment of sensor networks require a lot of nodes, and some deployment areas are dangerous for human. This paper proposes a deployment approach to solve the problems mentioned above. Our approach relies on the satellite images and the Virtual Force Algorithm (VFA). It first extracts the topography and elevation information of the deployment area from the high resolution satellite images, and then deploys nodes on them with an improved VFA. The simulation results show that the coverage rate of our method is approximately 15% higher than that of the classical VFA in complex environment.

Location information of sensor nodes plays a critical role in many wireless sensor network (WSN) applications and protocols. Although many localization algorithms have been proposed in recent years, they usually target at dense networks and perform poorly in sparse networks. In this paper, we propose two component-based localization algorithms that can localize many more nodes in sparse networks than the state-of-the-art solution. We first develop the Basic Common nodes-based Localization Algorithm, namely BCLA, which uses both common nodes and measured distances between adjacent components to merge components. BCLA outperforms CALL, the state-of-the-art component-based localization algorithm that uses only distance measurements to merge components. In order to further improve the performance of BCLA, we further exploit the angular information among nodes to merge components, and propose the Component-based Localization with Angle and Distance information algorithm, namely CLAD. We prove the merging conditions for BCLA and CLAD, and evaluate their performance through extensive simulations. Simulations results show that, CLAD can locate more than 90 percent of nodes in a sparse network with average node degree 7.5, while CALL can locate only 78 percent of nodes in the same scenario.

The efficiency of live Peer-to-Peer (P2P) streaming protocols depends on the appropriateness and the management abilities of their underlying overlay multicast. While a tree overlay structure confines transmission delays efficiently by maintaining deterministic delivery paths, an overlay mesh structure provides adequate resiliency to peers dynamics and easy maintenance. On the other hand, content freshness, playback fluidity and streaming continuity are still challenging issues that require viable solutions. In this paper, we propose a Hybrid Live P2P Streaming Protocol (HLPSP) based on a hybrid overlay multicast that integrates the efficiency of both the tree and mesh structures. Extensive simulations using OMNET++ are conducted to investigate the efficiency of HLPSP in terms of relevant performance metrics, and position HLPSP with respect to DenaCast the enhanced version of the well-known CoolStreaming protocol. Simulation results show that HLPSP outperforms DenaCast in terms of startup delay, end-to-end delay, play-back delay and data loss.

In this paper, we consider cooperative D2D communications in cellular networks. More precisely, a cellular user leases part of its spectrum to facilitate the D2D communication with a goal of improving the energy efficiency of a D2D pair. However the D2D pair is untrusted to the cellular user, such resource sharing may result in the information of this cellular user unsecured. In order to motivate the cellular user's generosity, this D2D pair needs to help the cellular user maintain a target secrecy rate. To address this issue, we formulate a joint spectrum and power allocation problem to maximize the energy efficiency of the D2D communication while guaranteeing the physical layer security of the cellular user. Then, a theorem is proved to indicate the best resource allocation strategy, and accordingly, an algorithm is proposed to find the best solution to this resource allocation problem. Numerical results are finally presented to verify the validity and effectiveness of the proposed algorithm.

We Relay-assisted cellular network architecture has been developed to cover cell-edge users and to improve capacity. However, the deployment of relay stations (RSs) in cellular networks may increase the total energy consumption. Though energy efficiency has become a major concern in cellular networks, little work has studied the energy efficiency of relay-assisted cellular networks by sleep scheduling. In this paper, a distributed base stations (BSs) sleep scheduling scheme in relay-assisted cellular networks is proposed. The goal is to maximize the energy efficiency under the spectral efficiency constraint. Firstly, whether the BSs should be sleeping or active is determined by the traffic profile. Then, the transmission powers of the active BSs are optimized within the game-theoretic framework, by using an interior-point method, so as to maximize the energy efficiency. Simulation results demonstrate that the effectiveness of the proposed scheme is superior to that turning on all the BSs without sleep scheduling.

An eye location based head posture recognition method is proposed in this paper. First, face is detected using skin color method, and eyebrow and eye areas are located based on gray gradient in face. Next, pupil circles are determined using edge detection circle method. Finally, head postures are recognized based on eye location information. The proposed method has high recognition precision and is robust for facial expressions and different head postures, and can be used in mouse operation. The experimental results reveal the validity of proposed method.

With the proposed principle of two-dimensional matrix bar code design based on masks, the whole surface of a 2D bar code is used for creating graphic patterns. Masks are a method of overlaying certain information with complete preservation of encoded information. In order to ensure suitable mask performance, it is essential to create a set of masks (mask folder) which are similar to each other. This ultimately allows additional error correction on the whole code level which is proven mathematically through an academic example of a QR code with a matrix of size $9{\times}9$. In order to create a mask folder, this article will investigate parameters based on Weber's law. With the parameters founded in the research, this principle shows how QR codes, or any other 2D bar code, can be designed to display two different messages. This ultimately enables a better description of a 2D bar code, which will improve users' visual recognition of 2D bar code purpose, and therefore users' greater enjoyment and involvement.

In texture-plus-depth format, depth map compression is an important task. Different from normal texture images, depth maps have less texture information, while contain many homogeneous regions separated by sharp edges. This feature will be employed to form an efficient depth map coding scheme in this paper. Firstly, the histogram of the depth map will be analyzed to find an appropriate threshold that segments the depth map into the foreground and background regions, allowing the edge between these two kinds of regions to be obtained. Secondly, the two regions will be encoded through rate distortion optimization with a shape adaptive wavelet transform, while the edges are lossless encoded with JBIG2. Finally, a depth-updating algorithm based on the threshold and the depth range is applied to enhance the quality of the decoded depth maps. Experimental results demonstrate the effective performance on both the depth map quality and the synthesized view quality.

Multiple Description (MD) coding is a promising alternative for the robust transmission of information over error-prone channels. Lattice vector quantization (LVQ) is a significant version of MD techniques to design an MD image coder. However, different from the traditional 2D texture image, the 3D depth image has its own special characteristics, which should be taken into account for efficient compression. In this paper, an optimized MDLVQ scheme is proposed in view of the characteristics of 3D depth image. First, due to the sparsity of depth image, the image blocks can be classified into edge blocks and smooth blocks, which are encoded by different modes. Furthermore, according to the boundary contents in edge blocks, the step size of LVQ can be regulated adaptively for each block. Experimental results validate the effectiveness of the proposed scheme, which show better rate distortion performance compared with the conventional MDLVQ.

In this paper, we propose a novel saliency detection framework based on illumination invariant features to improve the accuracy of the saliency detection under the different light conditions. The proposed algorithm is divided into three steps. First, we extract the illuminant invariant features to reduce the effect of the illumination based on the local sensitive histograms. Second, a preliminary saliency map is obtained in the CIE Lab color space. Last, we use the region growing method to fuse the illuminant invariant features and the preliminary saliency map into a new framework. In addition, we integrate the information of spatial distinctness since the saliency objects are usually compact. The experiments on the benchmark dataset show that the proposed saliency detection framework outperforms the state-of-the-art algorithms in terms of different illuminants in the images.

The Support Vector Data Description (SVDD) has achieved great success in anomaly detection, directly finding the optimal ball with a minimal radius and center, which contains most of the target data. The SVDD has some limited classification capability, because the hyper-sphere, even in feature space, can express only a limited region of the target class. This paper presents an anomaly detection algorithm for mitigating the limitations of the conventional SVDD by finding the minimum volume enclosing ellipsoid in the feature space. To evaluate the performance of the proposed approach, we tested it with intrusion detection applications. Experimental results show the prominence of the proposed approach for anomaly detection compared with the standard SVDD.

Network coding is promising to maximize network throughput and improve the resilience to random network failures in various networking systems. In this paper, the problem of providing efficient confidentiality for practical network coding system against a global eavesdropper (with full eavesdropping capabilities to the network) is considered. By exploiting a novel combination between the construction technique of systematic Maximum Distance Separable (MDS) erasure coding and traditional cryptographic approach, two efficient schemes are proposed that can achieve the maximum possible rate and minimum encryption overhead respectively on top of any communication network or underlying linear network code. Every generation is first subjected to an encoding by a particular matrix generated by two (or three) Vandermonde matrices, and then parts of coded vectors (or secret symbols) are encrypted before transmitting. The proposed schemes are characterized by tunable and measurable degrees of security and also shown to be of low overhead in computation and bandwidth.

Android is the world's most utilized smartphone OS which consequently, also makes it an attractive target for attackers. The most representative method of hacking used against Android apps is known as repackaging. This attack method requires extensive knowledge about reverse engineering in order to modify and insert malicious codes into the original app. However, there exists an easier way which circumvents the limiting obstacle of the reverse engineering. We have discovered a method of exploiting the Android code-signing process in order to mount a malware as an example. We also propose a countermeasure to prevent this attack. In addition, as a proof-of-concept, we tested a malicious code based on our attack technique on a sample app and improved the java libraries related to code-signing/verification reflecting our countermeasure.

People have transferred their business model from traditional commerce to e-commerce in recent decades. Both shopping and payment can be completed through the Internet and bring convenience to consumers and business opportunities to industry. These trade techniques are mostly set up based on the Secure Sockets Layer (SSL). SSL provides the security for transaction information and is easy to set up, which makes it is widely accepted by individuals. Although attackers cannot obtain the real content even when the transferred information is intercepted, still there is risk for online trade. For example, it is impossible to prevent credit card information from being stolen by virtual merchant. Therefore, we propose a new mechanism to solve such security problem. We make use of the disposable dynamic security code (DSC) to replace traditional card security code. So even attackers get DSC for that round of transaction, they cannot use it for the next time. Besides, we apply visual secret sharing techniques to transfer the DSC, so that interceptors cannot retrieve the real DSC even for one round of trade. This way, we can improve security of credit card transaction and reliability of online business. The experiments results validate the applicability and efficiency of the proposed mechanism.

Certificate-based signature (CBS) combines the advantages of both public key-based signature and identity-based signature, while saving from the disadvantages of drawbacks in both PKS and IBS. The insecure deployment of CBS under the hostile circumstances usually causes the exposure of signing key to be inescapable. To resist the threat of key leakage, we present a pairing-free key insulated CBS scheme by incorporating the idea of key insulated mechanism and CBS. Our scheme eliminates the costly pairing operations and as a matter of fact outperforms the existing key insulated CBS schemes. It is more suitable for low-power devices. Furthermore, the unforgeability of our scheme has been formally proven to rest on the discrete logarithm assumption in the random oracle model.

As the number of services available on the Web increases, it is vital to be able to identify which services can be trusted. Since there can be an extremely large number of potential services that offer similar functionality, it is challenging to select the right ones. Service requestors have to decide which services closelysatisfy their needs, and theymust worry about the reliability of the service provider. Although an individual service can be trusted, a composed service is not guaranteed to be trustworthy. In this paper, we present a trust model that supports service discovery and composition based on trustworthiness. We define a method to evaluate trust in order to discover trustworthy services. We also provide a method to perform trust estimation for dynamic service composition, and we present results of two experiments. The proposed model allows for service requestors to obtain the most trustworthy services possible. Our mechanism uses direct and indirect user experience to discover the trustworthiness of the services and service providers. Moreover, composing services based on quantitative trust measurements will allow for consumers to acquire a highly reliable service that meet their quality and functional requirements.