Large-scale online services parallelize sub-operations of a user's request across a large number of physical machines (service components) so as to enhance the responsiveness. Even a temporary spike in latency of any service component can notably inflate the end-to-end delay; therefore, the tail of the latency distribution of service components has become a subject of intensive research. The key characteristics of clouds such as elasticity and on-demand resource provisioning have made clouds attractive for hosting large-scale online services wherein VMs are the building blocks of services. However, adherence to traditional hypervisor scheduling policies has led to unpredictable CPU access latencies for virtual CPUs (vCPUs) that are responsible for performing network IO processes. This has resulted in poor and unpredictable performance for network IO, exacerbating VMs' long tail latencies and discouraging the hosting of large-scale parallel web services on virtualized clouds. This paper presents TerrierTail, a hypervisor CPU scheduler whose primary goal is to trim the tail of the latency distribution of individual VMs in virtualized clouds. In TerrierTail, we have modified the network driver to identify vCPUs that are responsible for performing network IO processes. Leveraging this information, the TerrierTail scheduler mitigates the CPU access latencies of such vCPUs using novel scheduling policies, resulting in a higher and more predictable network IO performance and therefore lower tail latency. TerrierTail's gains come at no measurable negative impacts on other performance attributes (e.g., fairness) or on the performance of VMs running other types of workloads (e.g., CPU-intensive VMs). A prototype implementation of TerrierTail in the Xen hypervisor substantially outperforms the default Credit scheduler of Xen. For example, TerrierTail mitigates the tail latency of a Memcached server by up to 53 percent and an RPC server by up to 50 percent at 99.9th percentile.

Extremely heterogeneous software stacks have encouraged the use of system virtualization technology for execution of composite high performance computing (HPC) applications to enable full utilization of extreme-scale HPC systems (ExaScale). Parts of composite applications, called loosely-coupled components, consist of a set of loosely-coupled CPU-intensive jobs. Jobs of loosely-coupled components run on a set of virtual machines (VMs), which in turn are distributed on physical machines. Co-location of VMs on physical machines, is the main source of interferences which cause uncertainty in jobs completion time. Motivated by this challenge, our main goal is to introduce an adaptive job scheduling method for VMs of loosely-coupled components in order to bound the negative impact of interferences. On the other hand, due to the abstraction of virtualization, job schedulers are unaware of the status of underlying physical machines. Introducing a scheme to dynamically reconfigure the job scheduler's parameters to inform scheduler about the true status of the physical machines, is our second goal. This paper presents a combination of ASSIGN-ROUTE online job scheduling and a reconfiguration technique allowing a given loosely-coupled component to balance its resource usage load, and thus improve the scaled execution of its loosely-coupled jobs. We prove that reconfiguration covers the virtualization unawareness in a way that the whole technique balances the load, comparable to the optimal load balancing for online deterministic unrelated parallel machine makespan minimization scheduling. We also show that the results of our experiments, support the theoretical achievements specially in case of scaled execution.

Blockage of some ion channels and in particular, the hERG (human Ether-a’-go-go-Related Gene) cardiac potassium channel delays cardiac repolarization and can induce arrhythmia. In some cases it leads to a potentially life-threatening arrhythmia known as Torsade de Pointes (TdP). Therefore recognizing drugs with TdP risk is essential. Candidate drugs that are determined not to cause cardiac ion channel blockage are more likely to pass successfully through clinical phases II and III trials (and preclinical work) and not be withdrawn even later from the marketplace due to cardiotoxic effects. The objective of the present study is to develop an SAR (Structure-Activity Relationship) model that can be used as an early screen for torsadogenic (causing TdP arrhythmias) potential in drug candidates. The method is performed using descriptors comprised of atomic NMR chemical shifts (13C and 15N NMR) and corresponding interatomic distances which are combined into a 3D abstract space matrix. The method is called 3D-SDAR (3-dimensional spectral data-activity relationship) and can be interrogated to identify molecular features responsible for the activity, which can in turn yield simplified hERG toxicophores. A dataset of 55 hERG potassium channel inhibitors collected from Kramer et al. consisting of 32 drugs with TdP risk and 23 with no TdP risk was used for training the 3D-SDAR model. An artificial neural network (ANN) with multilayer perceptron was used to define collinearities among the independent 3D-SDAR features. A composite model from 200 random iterations with 25% of the molecules in each case yielded the following figures of merit: training, 99.2%; internal test sets, 66.7%; external (blind validation) test set, 68.4%. In the external test set, 70.3% of positive TdP drugs were correctly predicted. Moreover, toxicophores were generated from TdP drugs. A 3D-SDAR was successfully used to build a predictive model for drug-induced torsadogenic and non-torsadogenic drugs based on 55 compounds. The model was tested in 38 external drugs.

Abstract Spelling errors in digital documents are often caused by operational and cognitive mistakes, or by the lack of full knowledge about the language of the written documents. Computer-assisted solutions can help to detect and suggest replacements. In this paper, we present a new string distance metric for the Persian language to rank respelling suggestions of a misspelled Persian word by considering the effects of keyboard layout on typographical spelling errors as well as the homomorphic and homophonic aspects of words for orthographical misspellings. We also consider the misspellings caused by disregarded diacritics. Since the proposed string distance metric is custom-designed for the Persian language, we present the spelling aspects of the Persian language such as homomorphs, homophones, and diacritics. We then present our statistical analysis of a set of large Persian corpora to identify the causes and the types of Persian spelling errors. We show that the proposed string distance metric has a higher mean average precision and a higher mean reciprocal rank in ranking respelling candidates of Persian misspellings in comparison with other metrics such as the Hamming, Levenshtein, Damerau–Levenshtein, Wagner–Fischer, and Jaro–Winkler metrics.

ABSTRACT One of the benefits of virtualization technology is the provision of secure and isolated computing environments on a single physical machine. However, the use of virtual machines for this purpose often degrades the overall system performance that is due to emulation costs, for example, packet filtering on every virtual machine. To allow virtual machines to be favorably used as before for the provision of secure environments but with comparably less performance degradation, we propose a new architecture called Alamut in this paper for restructuring any typical network intrusion detection system (NIDS) to run in a Xen‐based virtual execution environment. In the proposed architecture, primitive mechanisms for implementing the security concerns of typical NIDSs such as signature matching are placed at the kernel level of driver domain (dom0), whereas security policies and management modules are kept in user space of that domain. Separation of mechanisms from policies allows network packets to be verified at the kernel level first hand more efficiently without requiring costly context switches to push them to user space for validation. In addition, system administrators can easily define new policies at user level and determine on which virtual machines these policies should be enforced. A proof‐of‐concept implementation of Alamut has been prototyped on the Xen hypervisor using Bro open‐source NIDS. Experimental results show approximately 3.5‐fold increase in the overall system performance when our prototype is run compared with when Bro is run. Results also show 19% improvement in network throughput. The comparison of Alamut with Snort with the same set of signatures and attacks shows that our prototyped NIDS has lower processor utilization and has captured more packets in heavy network loads. Copyright © 2013 John Wiley & Sons, Ltd.

There is increased demand to run applications on mobile devices in recent years. Although many of these alluring applications are resource-intensive, they expect to get the same performance on mobile devices as on powerful non-mobile computers. On the other hand, considerations such as weight, size, and mobility impose constraints on mobile devices and restrict their processor speed, memory size and battery lifetime. Cyber foraging ameliorates this performance disparity by utilizing nearby non-mobile computers called surrogates to run the whole or parts of applications, which are offloaded from mobile devices. However, cyber foraging is not suitable for all circumstances. In this paper, we propose a mechanism to determine the best location, either a mobile device or best surrogate(s) around, to run an application by calculating the cost of offloading the task of running the application to each location according to the context's metrics such as specifications of mobile device, surrogates, network, and application. Experimental results show that our proposed mechanism almost always selects the best one between local execution of the application on the mobile device and task offloading to surrogate(s) according to the current input size of the application, with respect to latency and energy consumption.

Current distributed computing systems comprising of commodity computers like Network of Workstations (NOW) are obliged to deploy multicore processors to raise their performance. However, because multicore processors were absent when traditional standard programming models and APIs for distributed computing such as MPI and PVM were designed, traditional models are not suitable for programming multicore processors. In this paper, we argue in favor of a powerful programming model called the task-oriented programming model. This model is recently used for programming applications for both multicore processors and distributed computing systems such as computational grids. We argue that because of simplicity and the ability of automatic scaling of applications developed under this model, the task-oriented programming model fits the requirements of programming multicore enabled systems better than traditional models like message passing or multi-threading.

Software systems development nowadays has moved towards dynamic composition of services that run on distributed infrastructures aligned with continuous changes in the system requirements. Consequently, software developers need to tailor project specific methodologies to fit their methodology requirements. Process patterns present a suitable solution by providing reusable method chunks of software development methodologies for constructing methodologies to fit specific requirements. In this paper, we propose a set of high-level service-oriented process patterns that can be used for constructing and enhancing situational service-oriented methodologies. We show how these patterns are used to construct a specific service-oriented methodology for the development of a sample system.

Virtualization technology in the form of server consolidation makes running of hot-standby replicas on one system possible, while software rejuvenation provides proactive recovery of failure. Both technologies have been used to make systems more dependable. However, the deployment of rejuvenation in virtualized systems had been limited only to virtual machines (VMs) or only to virtual machine monitors (VMMs), requiring changes to applications too. We propose a new rejuvenation technique for high available virtualized systems that is applied at both VM and VMM levels and yet it does not require any modifications to applications. Our proposition leverages the encapsulation of an application into a VM using this new combinatory rejuvenation technique that uses a time-based policy for VMM and a prediction-based policy for VMs. To demonstrate how much it can improve system availability, the stochastic reward net-based models of a typical virtualized consolidated server in cases of using a prediction-based policy, using a time-based policy, and using the proposed rejuvenation technique are presented and compared. We show that our method has higher system availability and lower downtime cost.

Operating systems try to provide secure platforms using appropriate security mechanisms like DAC and MAC. In spite of this, information confidentiality is not totally provided when information flows in the program memory space. Programming language level security techniques have thus been introduced to provide secure information flow inside programs. Existing works on programming language level are problematic though because their information flow policies have not been integrated into the underlying system security policies. In this paper we propose a dynamic solution for tracking and enforcing information flow policies inside the Java framework that is integrated with a trusted operating system namely SELinux. Our solution focuses on internal structure of JVM, implicating no modification to Java programming language. Experimental results have shown a bearable runtime overhead on running programs.

Wireless sensor and actor networks (WSANs) are a set of coexistence sensors and actors connected wirelessly to perform cooperatively sensing and interaction to physical environment. Nowadays, WSANs are used in many important application areas. Main concern in all networks is connectivity of the network nodes, in WSANs because of majority of their applications, connectivity issue is even more vital. As WSANs deployment environment is not deterministic and mostly harsh, failure and partitioning of network upon actorpsilas failure is more probable. In this paper we put forward a distributed, proactive algorithm to restore actor-actor connectivity of WSANs that minimizes time of reconnecting the network and also total required movements of actors. We identify critical actor nodes and when a critical actor fails, we try to reconnect the network by relocating other actors. We validate our superiority through simulative experiments. Our approach serves significant decrease in total number of communicated messages through decision making for restoration planning and consequently decreases in network reconnection time compared to optimal cascading and other works. It also minimizes total movement of actors compared to other works.

The FT-CORBA standard that has been adopted by OMG in recent years introduces mechanisms in support of increasing the availability of systems. This standard provides an infrastructure to detect faults and replicate distributed objects. In this paper we are going to share our experiences on implementing an extended transaction service (OTSX) which provides a set of specific features in support of FT-CORBA standard. These extensions allow distributed applications developed on top of FT-CORBA to run atomic operations on multiple object groups and ignore any faults that may occur in any object. The role of some affecting parameters like object size and failure rate is also studied and reported in this paper.

Phishing is an increasing web attack both in volume and techniques sophistication. Blacklists are used to resist this type of attack, but fail to make their lists up- to-date. This paper proposes a new technique and architecture for a blacklist generator that maintains an up-to-date blacklist of phishing sites. When a page claims that it belongs to a given company, the company's name is searched in a powerful search engine like Google. The domain of the page is then compared with the domain of each of the Google's top- 10 searched results. If a matching domain is found, the page is considered as a legitimate page, and otherwise as a phishing site. Preliminary evaluation of our technique has shown an accuracy of 91% in detecting legitimate pages and 100% in detecting phishing sites.

Scientific applications like weather forecasting require high performance and fast response time. But this ideal requirement has always been constrained by peculiarities of underlying platforms specially distributed platforms. One such constraint is the efficiency of communication between geographically dispersed and physically distributed processes running these applications, that is the efficiency of inter process communication (IPC) mechanisms. This paper provides hard evidence that an operating system kernel-level implementation of IPC on multi-computers reduces the execution time of a weather forecasting model by nearly half on average compared to when the IPC mechanism is implemented at library level. A well known non-hydrostatic version of the Penn state/NCAR mesoscale model, called MM5, is executed on a networked cluster. The performance of MM5 is measured with two distributed implementations of IPC, a kernel-level implementation called DIPC2006 and a renowned library level implementation called MPI. It is both shown how and argued why the performance of MM5 on a DIPC2006 configured cluster is by far better than its performance on an MPI configured similar cluster. Even ignoring the favorable points of kernel-level implementations, like safety, privilege, reliability, and primitiveness, the insight is twofold. Scientist may look for more efficient distributed implementations of IPC to run their simulations faster, and computer engineers may try harder to develop more efficient distributed implementations of IPC for scientists.

One of the main challenges in pervasive systems is the efficient discovery of and access to resources in the dynamic environments of such systems. Existing resource discovery mechanisms are proved inefficient because they use broadcasting to communicate request messages for resources to peers. In this paper we present a more efficient mechanism for tuple-based pervasive systems by restricting such communications to a restricted number of social peers. Human behavioral patterns in social interactions to find their required resources known as peer to peer social networks are used instead. This is achieved by deploying a resource-aware routing mechanism. Each peer uses a special data structure to cache in locally the results of its previous searches for resources in the form of tuples. If it finds information on the peer holding its newly required resource in its local data structure, it only sends its request direct to that peer. Otherwise, it sends its request to its immediate peers, and so on to peers next to immediate peers if unsuccessful, until it finds the peer holding the resource. The resource discovery mechanism actually uses a globally accessible tuple space to store findings about all requests for resources in the form of tuples. This resolves the problem of keeping consistent the information cached locally by each peer. We ran exemplar scenarios on a prototyped implementation of our proposed mechanism in the Linda In a Mobile Environment (LIME) environment running on different hardware and under different operating systems.

Parallel programming and distributed programming are two solutions for scientific applications to provide high performance and fast response time in parallel systems and distributed systems. Parallel and distributed systems must provide inter process communication (IPC) mechanisms like message passing mechanism as underlying platforms to enable communication between local and especially geographically dispersed and physically distributed processes. Communication overhead is the major problem in these systems and there are a lot of efforts to develop more efficient message passing mechanisms or to improve the network communication speed. This paper provides hard evidence that an efficient implementation of message passing mechanism on multi-computers reduces the execution time of a molecular dynamics code. A well-known program for macromolecular dynamics and mechanics called CHARMm is executed on a networked cluster. The performance of CHARMm is measured with two distributed implementations of message passing, namely a kernel-level implementation called DIPC2006 and a renowned library level implementation called MPI. It is shown that the performance of CHARMm on a DIPC2006 configured cluster is by far better than its performance on an optimized MPI configured similar cluster. Even ignoring the favorable points of kernel-level implementations, like safety, privilege, reliability, and primitiveness, the insight is twofold. Scientists are nowadays faced with more computational complexity and look for more efficient systems and mechanisms. Efficient distributed IPC mechanisms have direct effect on running scientistspsila simulations faster, and computer engineers may try harder to develop more efficient distributed implementations of IPC.

Nowadays more and more business activities are operated through web and the web plays a vital role in the interests of both businesses and their shareholders. However, the very good features of web such as its popularity, accessibility and openness, has provided more opportunities for security breaches by malicious users. That is why the rate of successful attacks on web and web applications are increasing. Many approaches have been introduced so far to reduce the rate of successful attacks of many kinds. Any technique that can detect these vulnerabilities and mitigate the security problems of web applications is useful to organizations seeking for more reliability from the security viewpoint. In this paper we first introduce the control flow tampering attack, which is one of the notable attacks against web applications, and present our approach for countering this attack using web application firewall.

Recently, several flavors of formal methods (FMs) have been gaining industrial acceptance and production quality software tools have begun emerging. Domain engineering (DE) has been introduced as one of outstanding ideas in software development. It serves form al methods that provide a rigorous, mathematical based framework (domain model) for specifying, defining, and verifying systems in the software development. The increasing demands for extended products and services along with advances in lT industry have motivated researchers to create virtual organizations (VOs) in order to better respond to business opportunities and produce qualitative services and products. The purpose of this paper is to describe Virtual Organization and Domain engineering with introducing formal methods especially RAISE as a formal method that has been used successfully on diverse applications. Then, a primary formal model is presented using RAISE method and its language (RSI) formula for the improvement of VO creation process. Formal model presented in this paper is provable to implement. It improves reusability and reliability in such environments.

Recently, the use of wireless sensor networks has spread to applications areas that are not viable or cost-efficient to be run on other types of networks. The majority of these applications should be run continuously and reliably without interruption. Hence, the two significant quality factors that should be nowadays taken into account in developing wireless sensor networks applications are 'availability' and 'reliability' of application services. The specific characteristics and constraints of wireless sensor networks require a different interpretation of these two factors when developing applications for such networks. In this paper, we propose a middleware layer mechanism for satisfying these two factors. We propose an event-based middleware service that is specifically designed for wireless sensor networks in which a group of sensor nodes forms a cluster and a replicated service is run on each cluster head. The communication model among cluster members and cluster head is based on the publish/subscribe scheme. We show how the replicated services and communication model in cluster nodes increases the availability and reliability of applications running under the proposed middleware.

The CORBA Component Model (CCM) middleware provides a standard way to configure, manage and deploy distributed components. However, some current implementation of CCM is flawed with unreasonable communication overhead when components are in the same address space. Previous attempts to alleviate this drawback have tried to provide mechanisms for direct local communication of such components, but have sacrificed ORB services all together. Since such components do not communicate through ORB. They are deprived from ORB services such as events and naming. In case of need, programmers should implement such services themselves. This paper presents an alternative approach that likewise eliminates the unnecessary communication overhead between local components, but in addition provides them with local ORB-like services. A unit inside each container is made responsible for directing the communications between components within or outside the container. In case of local communications, requests are passed to the local components without ORB involvement. ORB-like services, namely events and naming, are provided by this unit locally for local components. Implementation results of the proposed approach with local event and naming services support show a favorable reduction of local communication overheads

One of the challenges in multi-agent systems is the prediction of the future state of the environment. This is because the future behavior of each agent and its relationship with other agents in the environment must be predicted according to an appropriate agent model. Such a prediction about the future of the environment in a large state space, like the RoboCup simulation environment, in which most agents act on the basis of uncertain knowledge, is quite hard. Given the above context, a novel multi-agent game presentation and analysis tool has been developed. One of the agents in this tool is responsible for the prediction of individual and team behaviors. To overcome the problem of uncertain knowledge, the prediction is only made for the simulated commentator who needs to anticipate the player agent receiving the ball after a shoot by another player agent. The predictor agent has been implemented both heuristically and with neural networks. Using the logged data form RoboCup 2002 simulation league, as our test data, the neural network approach had a higher success rate of true predictions than our heuristic simulation.

There are two main types of process scheduling algorithms commonly used in aircraft/spacecraft avionics systems. The first category consists of dynamic algorithms, which dynamically assign priorities to processes on the basis of runtime parameters. The second category consists of static algorithms, which statically determine priorities before runtime. The main disadvantage of applying dynamic process scheduling algorithms to avionics systems is the extra runtime overhead produced by these algorithms. This overhead is mainly related to the time required to sort active processes in the ready queue upon each process preemption or the arrival of each new process. The mentioned overhead encourages the use of static algorithms. But static algorithms have their own disadvantages. In fact, these algorithms bound the maximum available CPU utilization and have difficulties with non-periodic processes. This paper proposes and evaluates an approach to exploiting skewed associative memories in order to replace the time-consuming sorting operation by an efficient search operation. Both analytical models and simulation results show that the proposed approach can reduce the time complexity of the runtime overhead of dynamic scheduling algorithms (in terms of n the number of active processes) from O(nlogn) to O(n). This can considerably increase the performance of dynamic scheduling algorithms and make them much more feasible to be used in aircraft/spacecraft avionics systems.