Biblio

The proliferation of real-time cyber-physical systems (CPS) is making profound changes to our daily life. Many real-time CPSs are security and safety-critical because of their continuous interactions with the physical world. While the general perception is that the security protection mechanism deployment is often absent in real-time embedded systems, there is no existing empirical study that measures the adoption of these mechanisms in the ecosystem. To bridge this gap, we conduct a measurement study for real-time embedded firmware from both a security perspective and a real-time perspective. To begin with, we collected more than 16 terabytes of embedded firmware and sampled 1,000 of them for the study. Then, we analyzed the adoption of security protection mechanisms and their potential impacts on the timeliness of real-time embedded systems. Besides, we measured the scheduling algorithms supported by real-time embedded systems since they are also security-critical.

Fog computing extends the capability of cloud services to support latency sensitive applications. Adding fog computing nodes in proximity to a data generation/ actuation source can support data analysis tasks that have stringent deadline constraints. We introduce a real time, security-aware scheduling algorithm that can execute over a fog environment [1 , 2] . The applications we consider comprise of: (i) interactive applications which are less compute intensive, but require faster response time; (ii) computationally intensive batch applications which can tolerate some delay in execution. From a security perspective, applications are divided into three categories: public, private and semi-private which must be hosted over trusted, semi-trusted and untrusted resources. We propose the architecture and implementation of a distributed orchestrator for fog computing, able to combine task requirements (both performance and security) and resource properties.

The emerging time-sensitive applications, such as industrial automation, smart grids, and telesurgery, pose strong demands for enabling large-scale IP-based deterministic networks. The IETF DetNet working group recently proposes a Cycle Specified Queuing and Forwarding (CSQF) solution. However, CSQF only specifies an underlying device-level primitive while how to achieve network-wide flow scheduling remains undefined. Previous scheduling mechanisms are mostly oriented to the context of local area networks, making them inapplicable to the cyclic traffic in wide area networks. In this paper, we design the Cycle Tags Planning (CTP) mechanism, a first mathematical model to enable network-wide scheduling for cyclic traffic in large-scale deterministic networks. Then, a novel scheduling algorithm named flow offset and cycle shift (FO-CS) is designed to compute the flows' cycle tags. The FO-CS algorithm is evaluated under long-distance network topologies in remote industrial control scenarios. Compared with the Naive algorithm without using FO-CS, simulation results demonstrate that FO-CS improves the scheduling flow number by 31.2% in few seconds.

The steady growing trend of user demand in using various 4G mobile broadband applications obligates telecom operators to thoroughly plan a precise Quality of Service (QoS) contract with its subscribers. This directly reveals a challenge in figuring out a sophisticated behavior of radio resources (RBs) at the base station to effectively handle the oscillated loads to fulfill their QoS profiles. This paper elaborates on the above issue by analyzing the behavior of the downlink packet scheduling scheme and proposes a solution to bridge between the two major QoS indicators for Real-Time (RT) services, that are, throughput and delay. The proposed scheduling scheme emphasizes that a prior RBs planning indeed has an immense impact on the behavior of the deployed scheduling rule, particularly, when heterogeneous flows share the channel capacity. System-level simulations are performed to evaluate the proposed scheduling scheme in a comparative manner. The numerical results of throughput and delay assured that diverse QoS profiles can be satisfied in case of considering RBs planning.

Adapting parallel scheduling function in the design of multi-scheduling algorithm results significant impact in the operation of high performance parallel systems. The various methods of parallelizing scheduling functions are widely applied in traditional multiprocessor systems. In this paper a novel algorithm is introduced which works not only for parallel execution of jobs but also focuses the parallelization of scheduling function. It gives attention on reducing the execution time, minimizing the load balance performance by selecting the volume of tasks for migration in terms of packets. Jobs are grouped into packets consisting of 2n jobs which are scheduled in parallel. Thus, an enhancement in the scheduling mechanism by packet formation is made to carry out high utilization of underlying architecture with increased throughput. The proposed method is assessed on a desktop computer equipped with multi-core processors in cube based multiprocessor systems. The algorithm is implemented with different configuration of multi-core systems. The simulation results indicate that the proposed technique reduces the overall makespan of execution with an improved performance of the system.

In the existing scheduling algorithms of mimicry structure, the random algorithm cannot solve the problem of large vulnerability window in the process of random scheduling. Based on known vulnerabilities, the algorithm with diversity and complexity as scheduling indicators can not only fail to meet the characteristic requirements of mimic's endogenous security for defense, but also cannot analyze the unknown vulnerabilities and measure the continuous differences in time of mimic Executive Entity. In this paper, from the Angle of attack surface is put forward based on mimicry attack the mimic Executive Entity scheduling algorithm, its resources to measure analysis method and mimic security has intrinsic consistency, avoids the random algorithm to vulnerability and modeling using known vulnerabilities targeted, on time at the same time can ensure the diversity of the Executive body, to mimic the attack surface web server scheduling system in continuous time is less, and able to form a continuous differences. Experiments show that the minimum symbiotic resource scheduling algorithm based on time continuity is more secure than the random scheduling algorithm.

The disadvantages and inextensibility of the traditional network require more novel thoughts for the future network architecture, as for ICN (Information-Centric Network), is an information centered and self-caching network, ICN is deeply rooted in the 5G era, of which concept is user-centered and content-centered. Although the ICN enables cache replacement of content, an information distribution scheduling algorithm is still needed to allocate resources properly due to its limited cache capacity. This paper starts with data popularity, information epilepsy and other data related attributes in the ICN environment. Then it analyzes the factors affecting the cache, proposes the concept and calculation method of Gene value. Since the ICN is still in a theoretical state, this paper describes an ICN scenario that is close to the reality and processes a greedy caching algorithm named GDGCA (Gene Driven Greedy Caching Algorithm). The GDGCA tries to design an optimal simulation model, which based on the thoughts of throughput balance and satisfaction degree (SSD), then compares with the regular distributed scheduling algorithm in related research fields, such as the QoE indexes and satisfaction degree under different Poisson data volumes and cycles, the final simulation results prove that GDGCA has better performance in cache scheduling of ICN edge router, especially with the aid of Information Gene value.

Mixed-criticality scheduling theory (MCSh) was developed to allow for more resource-efficient implementation of systems comprising different components that need to have their correctness validated at different levels of assurance. As originally defined, MCSh deals exclusively with pre-runtime verification of such systems; hence many mixed-criticality scheduling algorithms that have been developed tend to exhibit rather poor survivability characteristics during run-time. (E.g., MCSh allows for less-important (“Lo-criticality”) workloads to be completely discarded in the event that run-time behavior is not compliant with the assumptions under which the correctness of the LO-criticality workload should be verified.) Here we seek to extend MCSh to incorporate survivability considerations, by proposing quantitative metrics for the robustness and resilience of mixed-criticality scheduling algorithms. Such metrics allow us to make quantitative assertions regarding the survivability characteristics of mixed-criticality scheduling algorithms, and to compare different algorithms from the perspective of their survivability. We propose that MCSh seek to develop scheduling algorithms that possess superior survivability characteristics, thereby obtaining algorithms with better survivability properties than current ones (which, since they have been developed within a survivability-agnostic framework, tend to focus exclusively on pre-runtime verification and ignore survivability issues entirely).

Compared to ordinary Internet applications, the transfer of scientific data flows often has higher requirements for network performance. The network security devices and systems often affect the efficiency of scientific data transfer. As a new type of network architecture, Software-defined Networking (SDN) decouples the data plane from the control plane. Its programmability allows users to customize the network transfer path and makes the network more intelligent. The Science DMZ model is a private network for scientific data flow transfer, which can improve performance under the premise of ensuring network security. This paper combines SDN with Science DMZ, designs and implements an SDN-based traffic scheduling algorithm considering the load of link. In addition to distinguishing scientific data flow from common data flow, the algorithm further distinguishes the scientific data flows of different applications and performs different traffic scheduling of scientific data for specific link states. Experiments results proved that the algorithm can effectively improve the transmission performance of scientific data flow.

The main challenge of ultra-reliable machine-to-machine (M2M) control applications is to meet the stringent timing and reliability requirements of control systems, despite the adverse properties of wireless communication for delay and packet errors, and limited battery resources of the sensor nodes. Since the transmission delay and energy consumption of a sensor node are determined by the transmission power and rate of that sensor node and the concurrently transmitting nodes, the transmission schedule should be optimized jointly with the transmission power and rate of the sensor nodes. Previously, it has been shown that the optimization of power control and rate adaptation for each node subset can be separately formulated, solved and then used in the scheduling algorithm in the optimal solution of the joint optimization of power control, rate adaptation and scheduling problem. However, the power control and rate adaptation problem has been only formulated and solved for continuous rate transmission model, in which Shannon's capacity formulation for an Additive White Gaussian Noise (AWGN) wireless channel is used in the calculation of the maximum achievable rate as a function of Signal-to-Interference-plus-Noise Ratio (SINR). In this paper, we formulate the power control and rate adaptation problem with the objective of minimizing the time required for the concurrent transmission of a set of sensor nodes while satisfying their transmission delay, reliability and energy consumption requirements based on the more realistic discrete rate transmission model, in which only a finite set of transmit rates are supported. We propose a polynomial time algorithm to solve this problem and prove the optimality of the proposed algorithm. We then combine it with the previously proposed scheduling algorithms and demonstrate its close to optimal performance via extensive simulations.

This paper proposes a new cross-layer based packet scheduling scheme for multimedia traffic in satellite Long Term Evolution (LTE) network which adopts MIMO technology. The Satellite LTE air interface will provide global coverage and hence complement its terrestrial counterpart in the provision of mobile services (especially multimedia services) to users across the globe. A dynamic packet scheduling scheme is very important towards actualizing an effective utilization of the limited available resources in satellite LTE networks without compromise to the Quality of Service (QoS) demands of multimedia traffic. Hence, the need for an effective packet scheduling algorithm cannot be overemphasized. The aim of this paper is to propose a new scheduling algorithm tagged Cross-layer Based Queue-Aware (CBQA) Scheduler that will provide a good trade-off among QoS, fairness and throughput. The newly proposed scheduler is compared to existing ones through simulations and various performance indices have been used. A land mobile dual-polarized GEO satellite system has been considered for this work.