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Analyzing blockchain protocols is a notoriously difficult task due to the underlying large scale distributed networks. To address this problem, stochastic model-based approaches are often utilized. However, the abstract models in prior work turn out not to be adoptable to consortium blockchains as the consensus of such a blockchain often consists of multiple processes. To address the lack of efficient analysis tools, we propose a queueing network-based method for analyzing consistency properties of consortium blockchain protocols in this article. Our method provides a way to evaluate the performance of the main stages in blockchain consensus. We apply our framework to the Hyperledger Fabric system and recover key properties of the blockchain network. Using our method, we analyze the security properties of the ordering mechanism and the impact of delaying endorsement messages in consortium blockchain protocols. Then an upper bound is derived of the damage an attacker could cause who is capable of delaying the honest players’ messages. Based on the proposed method, we employ analytical derivations to investigate both the security and performance features, and corroborate close agreement with measurements on a wide-area network testbed running the Hyperledger Fabric blockchain. With the proposed method, designers of future blockchains can provide a more rigorous analysis of their consortium blockchain schemes.

Mobile phones and tablets are becoming the primary platform of choice. However, these systems still suffer from limited battery and computation resources. A popular technique in mobile edge systems is computing outsourcing that augments the capabilities of mobile systems by migrating heavy workloads to resourceful clouds located at the edges of cellular networks. In the multi-site scenario, it is possible for mobile devices to save more time and energy by offloading to several cloud service providers. One of the most important challenges is how to choose servers to offload the jobs. In this paper, we consider a multi-site decision problem. We present a scheme to determine the proper assignment probabilities in a two-site mobile-edge computing system. We propose an open queueing network model for an offloading system with two servers and put forward performance metrics used for evaluating the system. Then in the specific scenario of a mobile chess game, where the data transmission is small but the computation jobs are relatively heavy, we conduct offloading experiments to obtain the model parameters. Given the parameters as arrival rates and service rates, we calculate the optimal probability to assign jobs to offload or locally execute and the optimal probabilities to choose different cloud servers. The analysis results confirm that our multi-site offloading scheme is beneficial in terms of response time and energy usage. In addition, sensitivity analysis has been conducted with respect to the system arrival rate to investigate wider implications of the change of parameter values.

Modern remote sensing (RS) image application systems often distribute image processing tasks among multiple data centers and then gather the processed images from each center to efficiently synthesize the final product. In this paper, we exploit the edge-cloud architecture to design and implement a novel RS image service system, called RS-pCloud, which leverages the Peer-to-Peer (P2P) model to integrate multiple data centers and their associated edge networks. The data center as cloud platform is responsible for the storage and processing of original RS images, as well as the storage of partial processed images while the edge network is mainly for caching and sharing the processed images. With this design, RS-pCloud not only achieves the load sharing of processing works but also attains the data efficiency among the edges at the same time, which in turn improves the performance of the image processing and reduce the cost of the data transmission as well. RS-pCloud is designed to be used in a transparent way where it receives a query task from the user through a certain cloud platform, split the task into different sub-tasks, according to the location of the data they required, and then distribute the sub-tasks to corresponding clouds for near-data processing, the returned results from each cloud are first cached in specific edge for further sharing and then gathered at the client to synthesize the final product. We implemented and deployed RS-pCloud on three clusters in conjunction with an edge network to show its performance advantages over traditional single-cluster systems.

The ever-increasing demand for more reliable and flexible energy supply for customers has pushed up the Microgrids (MGs) to the center stage in the developments of distribution networks. The integration of the MGs can provide the customers with better service compared with traditional radial-configured distribution networks with a single generation source. Yet, to motivate more and more MGs developer and practitioner to trade with the distribution network and thus, to improve the quality-of-service of energy consumers, a proper mechanism for energy trading is more than necessary. In this paper, we first analyzed the energy-supply cost for an MG, including power generation cost, distribution cost, transaction cost and service cost. Then we proposed a mechanism of energy trading for multiple MGs integrated distribution network, and this mechanism aims at maximizing the overall benefits of the MG. A case study is also provided to demonstrate that the proposed mechanism is effective and can be used to guide the energy trading of MGs with the quality of service for energy supply being taken into consideration.

The integration of large-scale renewable energy has brought great challenges for the control and operation of power systems. In order to accommodate the renewable power as much as possible, the system operators should properly coordinate the conventional generators such as thermal units with renewable sources to operate the power system efficiently while satisfying the constraints enforced by energy consummation as well as regulation rules. In this paper, an optimal power dispatch method is proposed for the wind-coal intensive power system by considering both deep cycling and carbon emission cost of the thermal units. To this end, the deep cycling cost function is proposed to properly signify the operation cost of thermal units that are operating in the deep cycling states while the carbon emission cost function is presented to accommodate the charge for emission. The optimal dispatch problem is formulated as a quadratic optimization problem, and the corresponding solution of this optimization problem can ensure the feasible and economic operation of power systems with high penetration of renewable energy. The case studies prove the effectiveness of the proposed method.

The integration of large-scale renewable energy has brought great challenges for the control and operation of power systems. In order to accommodate the renewable power as much as possible, the system operators should properly coordinate the conventional generators such hydro and thermal units in the system. In this paper, a peak regulation strategy is proposed for the control of multiple heterogeneous generators to maximize the renewable energy usage ratio in a regional power system. To this end, first the hydro generators is utilized to alleviate the stress for peak regulation due to dramatic fluctuation of the renewable power. Then an optimization model is established with objective function being maximizing the peak regulation capability of the system in a weekly period. The obtained optimal solution of the model can ensure the peak regulation requirement of the system during the whole planning-period while avoiding the frequent switch of on-off operation for the thermal units within the system.

Bring Your Own Device (BYOD) security is a concern for many companies' IT departments. Many corporations implement a “secure container” solution that provides full separation of work and personal data on mobile devices to mitigate the dangers brought by BYOD. In this paper, we perform an empirical comparison between two popular secure containers for Android: Samsung Knox and IBM MaaS360. We first conduct benchmark tests to compare these two containers. Then in order to quantitatively assess the security property of these containers, we propose a measurement method based on a simulating attack. Our experimental results show that performance of compute-intensive applications in the Knox container will be affected drastically compared with when they are running on the device (outside the container), while for memory-intensive applications, performance will not deteriorate much in Knox and MaaS360 containers. We also found that with an overhead of 3.3 ms (0.58%) in mean response time, Knox container can extend the mean time to security failure (MTTSF) by 109.6 min (878%). Within the MaaS360 container, the MTTSF is prolonged by 10.2 min (81.4%) but the response time is 3.3 ms (0.58%) longer per job than without containers.

Wireless sensor networks (WSNs) have recently gained popularity for a wide spectrum of applications. Monitoring tasks can be performed in various environments. This may be beneficial in many scenarios, but it certainly exhibits new challenges in terms of security due to increased data transmission over the wireless channel with potentially unknown threats. Among possible security issues are timing attacks, which are not prevented by traditional cryptographic security. Moreover, the limited energy and memory resources prohibit the use of complex security mechanisms in such systems. Therefore, balancing between security and the associated energy consumption becomes a crucial challenge. This paper proposes a secure scheme for WSNs while maintaining the requirement of the security-performance tradeoff. In order to proceed to a quantitative treatment of this problem, a hybrid continuous-time Markov chain (CTMC) and queueing model are put forward, and the tradeoff analysis of the security and performance attributes is carried out. By extending and transforming this model, the mean time to security attributes failure is evaluated. Through tradeoff analysis, we show that our scheme can enhance the security of WSNs, and the optimal rekeying rate of the performance and security tradeoff can be obtained. View Full-Text

In practical localization system design, researchers need to consider several aspects to make the positioning efficiently and effectively, e.g., the available auxiliary information, sensing devices, equipment deployment and the environment. Then, these practical concerns turn out to be the technical problems, e.g., the sequential position state propagation, the target-anchor geometry effect, the Non-line-of-sight (NLOS) identification and the related prior information. It is necessary to construct an efficient framework that can exploit multiple available information and guide the system design. In this paper, we propose a scalable method to analyze system performance based on the Cramér–Rao lower bound (CRLB), which can fuse all of the information adaptively. Firstly, we use an abstract function to represent all of the wireless localization system model. Then, the unknown vector of the CRLB consists of two parts: the first part is the estimated vector, and the second part is the auxiliary vector, which helps improve the estimation accuracy. Accordingly, the Fisher information matrix is divided into two parts: the state matrix and the auxiliary matrix. Unlike the theoretical analysis, our CRLB can be a practical fundamental limit to denote the system that fuses multiple information in the complicated environment, e.g., recursive Bayesian estimation based on the hidden Markov model, the map matching method and the NLOS identification and mitigation methods. Thus, the theoretical results are approaching the real case more. In addition, our method is more adaptable than other CRLBs when considering more unknown important factors. We use the proposed method to analyze the wireless sensor network-based indoor localization system. The influence of the hybrid LOS/NLOS channels, the building layout information and the relative height differences between the target and anchors are analyzed. It is demonstrated that our method exploits all of the available information for the indoor localization systems and serves as an indicator for practical system evaluation. View Full-Text