Sharif Digital Repository

Adopting multicore platforms is a general trend in real-time embedded systems. However, integrating tasks with different real-time constraints into a single platform presents new design challenges. While it must be guaranteed that hard real-time tasks are able to meet their deadline even in worst case scenarios, firm real-time tasks should be scheduled in a way to achieve high system utilization in order to provide a better quality of service. In this paper, we propose a scheduling scheme for frame-based tasks on real-time multicore embedded systems which is able to guarantee the schedulability of the hard real-time tasks, while it improves the number of executed firm real-time tasks.... 

An increasing trend for reducing cost, space, and weight leads to modern embedded systems that execute multiple tasks with different criticality levels on a common hardware platform while guaranteeing a safe operation. In such mixed-criticality (MC) systems, multiple worst case execution times (WCETs) are defined for each task, corresponding to the system operation mode to improve the MC system's timing behavior at runtime. Determining the appropriate WCETs for lower criticality (LC) modes is nontrivial. On the one hand, considering a very low WCET for tasks can improve the processor utilization by scheduling more tasks in that mode, on the other hand, using a larger WCET ensures that the... 

An increasing trend for reducing cost, space, and weight leads to modern embedded systems that execute multiple tasks with different criticality levels on a common hardware platform while guaranteeing a safe operation. In such Mixed-Criticality (MC) systems, multiple Worst-Case Execution Times (WCETs) are defined for each task, corresponding to system operation mode to improve the MC system’s timing behavior at run-time. Determining the appropriate WCETs for lower criticality modes is non-trivial. On the one hand, considering a very low WCET for tasks can improve the processor utilization by scheduling more tasks in that mode, on the other hand, using a larger WCET ensures that the mode... 

In this paper, two different important quality metrics, clearance and execution time, for motion planning of mobile robots are studied. Then a new approach, called Clearance-Based Probabilistic Roadmap Method (CBPRM (c)), is proposed which in contrast to VV(c) method, Visibility-Voronoi with clearance c, beside satisfaction of a predefined clearance is very efficient in running time. This provides the CBPRM (c) to be applicable in dynamic environments which require realtime approaches. Experiments showed that the CBPRM(c) is able to generate paths with very low execution time considering determined clearance. © 2008 IEEE  

Worst case execution time and energy consumption are two of the most important design constraints of real-time embedded systems. Many recent studies have tried to improve the memory subsystem of embedded systems by using emerging non-volatile memories. However, accessing these memories imposes performance and energy overhead and using them as the code memory could increase the worst case execution time of the system. In this paper, a new code memory architecture for non-volatile memories is proposed which reduces the effective memory access latency by employing memory access interleaving technique. Unlike common instruction access latency improvement techniques such as prefetching and... 

In recent years, Android is widely used in cell phones. Dalvik is the virtual machine which is embedded inside the Android operating system, and executes the Android-based applications. Thus, improving efficiency of the Dalvik virtual machine plays an important role in optimizing performance of android-based mobile phones. In this paper, we present a comprehensive analysis of the Dalvik bytecodes and their frequency of use in common Android applications and use the results to determine the most frequently used bytecodes in Dalvik virtual machine to identify best targets for improvement. Our analysis showed that over 82% of total execution time of our Android benchmarks is spent by only 5... 

The aim of this paper is to propose a scheduling method to consider reliability along with makespan in grid computing systems. The reliability of task execution is considered in the proposed method to increase the chance of running large-scale and computationally intensive workflows successfully. To handle situations in which a resource failure in a possible scheduling solution occurs, the proposed method finds a collection of scheduling solutions instead of only one solution to run the workflow. It leads to have chance to run an alternative scheduling solution that is not using the failed resource. To find the most optimized scheduling solutions, we exploit the lately developed... 

Recently, there has been a growing attention in frequent itemset mining in distributed systems. In this paper, we present an algorithm to extract frequent itemsets from large distributed datasets. Our algorithm uses gossip as the communication mechanism and does not rely on any central node. In gossip based communication, nodes repeatedly select other random nodes in the system, and exchange information with them. Our algorithm proceeds in rounds and provides all nodes with the required support counts of itemsets, such that each node is able to extract the global frequent itemsets. For local iteration and generation of candidate itemsets, a trie data structure is used, which facilitates the... 

In this paper, we address the matrix completion problem and propose a novel algorithm based on a smoothed rank function (SRF) approximation. Among available algorithms like FPCA and OptSpace, there is no solution that can simultaneously cover wide range of easy and hard problems. This new algorithm provides accurate results in almost all scenarios with a reasonable run time. It especially has low execution time in hard problems where other methods need long time to converge. Furthermore, when the rank is known in advance and is high, our method is very faster than previous methods for the same accuracy. The main idea of the algorithm is based on a continuous and differentiable approximation... 

Compile-time optimizations play an important role in the efficient design of real-time embedded systems. Usually, compile-time optimizations are designed to reduce average-case execution time (ACET). While ACET is a main concern in high-performance computing systems, in real-time embedded systems, concerns are different and worst-case execution time (WCET) is much more important than ACET. Therefore, WCET reduction is more desirable than ACET reduction in many real-time embedded systems. In this article, we propose a compile-time optimization method aimed at reducing WCET in real-time embedded systems. In the proposed method, based on the predicated execution capability of embedded... 

A major challenge organizations face when hosting or moving their data to the Cloud is how to support complex queries over outsourced data while preserving their confidentiality. In principle, encryption-based systems can support querying encrypted data, but their high complexity has severely limited their practical use. In this paper, we propose an efficient yet secure secret sharing-based approach for outsourcing relational data to honest-but-curious data servers. The problem with using secret sharing in a data outsourcing scenario is how to efficiently search within randomly generated shares. We present multiple partitioning methods that enable clients to efficiently search among shared... 

Data skew, which is the result of uneven distribution of data among tasks in big data processing frameworks such as MapReduce, causes significant variation in the execution time of tasks and makes their placement on computing resources more challenging. Moreover, with the proliferation of big data processing in the cloud, the interference among virtual machines co-located on the same physical machine exacerbates the aforementioned variation. To tackle this challenge, we propose Locality and Interference aware Portfolio-based Task Assignment (LIPTA) approach. LIPTA leverages the modern portfolio theory to mitigate the variation in execution time of tasks while considering the interference of... 

Worst case execution time and energy consumption are two of the most important design constraints of real-time embedded systems and memory subsystem has a major impact on both of them. Therefore, many recent studies have tried to improve the memory subsystem of embedded systems by using emerging non-volatile memories instead of conventional memories such as SRAM and DRAM. Indeed, the low leakage power dissipation and improved density of emerging non-volatile memories make them prime candidates for replacing the conventional memories. However, accessing these memories imposes performance and energy overhead and using them as the instruction memory could increase the worst case execution time,... 

In Mixed-Criticality (MC) systems, there are often multiple Worst-Case Execution Times (WCETs) for the same task, corresponding to system operation mode. Determining the appropriate WCETs for lower criticality modes is non-trivial; while on the one hand, a low WCET for a mode can improve the processor utilization in that mode, on the other hand, using a larger WCET ensures that the mode switches are minimized, thereby maximizing the quality-of-service for all tasks, albeit at the cost of processor utilization. Although there are many studies to determine WCET in the highest criticality mode, no analytical solutions are proposed to determine WCETs in other lower criticality modes. In this... 

As a matter of course, the unprecedented ascending penetration of distributed energy resources, mainly harvesting renewable energies, is a direct consequence of environmental concerns. This type of energy resource brings about more uncertainties in power system operation and planning; consequently, it necessitates probabilistic analyses of the system performance. This paper develops a new approach for probabilistic load flow (PLF) evaluation using the unscented transformation (UT) method. The UT method is recognized as a powerful approach in assessing stochastic problems with/without correlated uncertain variables. The capability of the UT method in modeling correlated uncertain variables is... 

In this paper, a model for the optimal placement of contingency-constrained phasor measurement units (PMUs) in electric power networks is presented. The conventional complete observability of power networks is first formulated and then, different contingency conditions in power networks including measurement losses and line outages are added to the main model. The communication constraints which would limit the maximum number of measurements associated with each installed PMU is considered as measurement limitations. The relevant formulations are also proposed to make the model more comprehensive. The IEEE standard test systems are examined for the applicability of proposed model. The... 

As a matter of course, the unprecedented ascending penetration of distributed energy resources, mainly harvesting renewable energies, is a direct consequence of environmental concerns. This type of energy resource brings about more uncertainties in power system operation and planning; consequently, it necessitates probabilistic analyses of the system performance. This paper develops a new approach for probabilistic load flow (PLF) evaluation using the unscented transformation (UT) method. The UT method is recognized as a powerful approach in assessing stochastic problems with/without correlated uncertain variables. The capability of the UT method in modeling correlated uncertain variables is...