Soft Real Time Research Articles

MOEME: Real-time Mobility and Orientation Estimation for Mobile Environments

Knowledge of user movement in mobile environments paves the way for intelligent resource allocation and event scheduling for a variety of applications. Existing schemes for estimating user mobility are limited in their scope as they rely on repetitive patterns of user movement. Such patterns neither exist not easy to recognize in soft-real time, in open environments such as parks, malls, or streets. We propose a novel scheme for Real-time Mobility and Orientation Estimation for Mobile Environments (MOEME). MOEME employs the concept of temporal distances and uses logistic regression to make real time estimations about user movement. MOEME is also used to make predictions about the absolute orientation of users. MOEME relies only on opportunistic message exchange and is fully distributed, scalable, and requires neither a central infrastructure nor Global Positioning System. MOEME has been tested on real world and synthetic mobility traces—makes predictions about direction and count of users with up to 90% accuracy, enhances successful video downloads in shared environments.

A new RR Scheduling Approach for Real Time Systems using Fuzzy Logic

Round Robin scheduling algorithm is the widely used scheduling algorithm in multitasking. It ensures fairness and starvation free execution of processes. It performs optimally for time sharing systems, but because of its larger waiting time, turnaround time and greater number of context switches it is not suitable for soft real time systems. The main objective of this paper is to develop a way in which the Round Robin algorithm can be modified for implementation in real time and embedded systems by minimizing its average waiting time, average turnaround time and context switching rate. The paper discusses a fuzzy based CPU scheduling algorithm. A set of fuzzy rules is defined. Each process is assigned a new priority based on its externally defined priority, relative remaining CPU burst time and relative waiting time. General Terms Algorithms, CPU scheduling

RER: a real time energy efficient routing protocol for query-based applications in wireless sensor networks

Energy-aware routing protocols can be classified into two categories, energy savers and energy balancers. Energy saver protocols are used to minimize the overall energy consumed by a wireless sensor network (WSN), while energy balancer protocols efficiently distribute the consumption of energy throughout the network. Energy saver protocols are not necessarily good at balancing energy consumption and energy balancer protocols are not always efficient at reducing energy consumption. On the other hand, although delay is another important factor for WSNs energy-aware protocols do not take care of it. This paper proposes a real time energy efficient routing protocol for query-based applications in WSNs, which offers an efficient trade-off between traditional energy balancing and energy saving objectives while supporting a soft real time packet delivery. This is achieved by means of fuzzy sets and learning automata techniques along with zonal broadcasting to decrease total energy consumption.

Optimal Semi-Partitioned Scheduling in Soft Real-Time Systems

Semi-partitioned real-time scheduling algorithms extend partitioned ones by allowing a (usually small) subset of tasks to migrate. The first such algorithm to be proposed was directed at soft real-time (SRT) sporadic task systems where bounded deadline tardiness is acceptable. That algorithm, called EDF-fm, has the desirable property that migrations are boundary-limited, i.e., they can only occur at job boundaries. However, it is not optimal because per-task utilization restrictions are required. In this paper, a new optimal semi-partitioned scheduling algorithm for SRT sporadic task systems is proposed that eliminates such restrictions. This algorithm, called EDF-os, preserves the boundary-limited property. In overhead-aware schedulability experiments presented herein, EDF-os proved to be better than all other tested alternatives in terms of schedulability in almost all considered scenarios. It also proved capable of ensuring very low tardiness bounds, which were near zero in most considered scenarios.

MUBaaS: mobile ubiquitous brokerage as a service

The use of multiple personalized mobile devices (e.g., smartphones and tablets) is on the increase. As such, users expect to access several network-based services across their n-devices. Previous studies proposed Ubiquitous Cloud Computing (UCC) where a single user or service consumer is facilitated to access multiple services from n-devices. However, seamless synchronization of data between the multiple devices can be hindered by intermittent loss of connectivity in mobile wireless networks due to user mobility. Another source of latency is non-scalable architectures that tend to be overburdened during peak loads. This work proposes a cloud-based application middleware, called Mobile Ubiquitous Brokerage as a Service (MUBaaS), which enables n-devices of a user to access multiple cloud services end-points in soft-real time. This is achieved by proposing distributed brokers that coordinates the transactions of the user while taking load balancing into account. Pilot evaluations of the proposed architecture prove real-time application synchronization with reasonable scalability.

Design and Analysis of EDF Scheduling Algorithm for a Chosen Network Traffic Problem: Implementation and Simulation Analysis

Abstract Workstations, CPU etc are in a period of transition, moving from a relatively slow network links and data oriented services to a high set fibre optic services and more diverse services. As such many of the hard and soft real time will not only demand high bandwidth but also a predictable and guarantee Quality of Service (QoS) along side, which is not offered in a best effort network (BE). The provision and terms of (QoS) to real-time applications is a key issue in promising broadband packet switched networks and network of other sorts. Applications such as voice and video typically require QoS guarantees in terms of end-to-end data transfer delays. Supporting the diverse and of course, heterogeneous delay requirements of applications with widely varying characteristics requires packet scheduling schemes more sophisticated than First-In-First-Out (FIFO) at each switch in the network(2) are one of most accepted examples of such scheduling schemes. This points to the convincing need for a QoS, which apportion a high network utilization to be realized. In this paper, we focus on the EDF scheduling scheme, since it is known to provide the optimal delay performance (2), in the deterministic environment, and can for this reason be expected to perform well in the real time setting as well. The large amount of bandwidth as promised by the future network also offer the integration of real time applications, hard or soft.

Modified RR Algorithm with Dynamic Time Quantum for Externally Prioritized Tasks

The objective of this paper is to modify Round Robin scheduling for soft real time systems. It introduces a variation of round robin algorithm which can schedule tasks considering their priorities in a round robin fashion. Simple Round Robin scheduling algorithm and Priority scheduling algorithm, both have their own drawbacks. The proposed algorithm removes the drawbacks of Round Robin scheduling and Priority scheduling. The proposed scheduling algorithm calculates different time slices for individual processes considering their priorities. Experimental analysis reveals that the proposed algorithm produces better average turnaround time, average waiting time and less number of context switches than some existing algorithms useful for interactive systems. KeywordsOperating System; Scheduling; Round Robin Algorithm; Context switch; Turnaround time; Average Waiting time __________________________________________________*****_________________________________________________

PID Controllers Design Applied to Positioning of Ball on the Stewart Platform

Abstract The paper presents the design and practical implementation of PID controllers for a Stewart platform. The platform uses a resistance touch panel as a sensor and servo motors as actuators. The complete control system stabilizing the ball on the platform is realized with the Arduino microcontroller and the Matlab/Simulink software. Two processes required to acquire measurement signals from the touch panel in two perpendicular directions X and Y, are discussed. The first process includes the calibration of the touch panel, and the second process - the filtering of measurement signals with the low pass Butterworth filter. The obtained signals are used to design the algorithm of the ball stabilization by decoupling the global system into two local subsystems. The algorithm is implemented in a soft real time system. The parameters of both PID controllers (PIDx and PIDy) are tuned by the trial-error method and implemented in the microcontroller. Finally, the complete control system is tested at the laboratory stand.

Energy Efficient Scheduling Algorithm for Soft Real Time System with High Deadline Meeting Rate on Overload

The fact that earliest deadline first (EDF) scheduling algorithm behaves unpredictably during overload is an old and existing issue in the field of real time system. In this paper, a new software process scheduling algorithm for soft real time applications is presented. The algorithm is formulated by means of logical reasoning and excessive simulation method. This method is adopted due to the fact that the problem of scheduling a set of periodic task on single processor using non-preemptive scheme is NP-hard in the strong sense. The new algorithm, with inherently less computational complexity is found to improve in power consumption by almost 50 percent at the peak of practical overload which is at 150 percent of system load. At the same system load, the new algorithm also gives a minimum of 16 percent improvement in deadline meeting rate (DMTR) as compared to EDF. Design and formulation of the new algorithm along with graphical results of the power consumption level and the level of the deadline meeting rate of both algorithms will be presented and discuss in detail.

Traffic Control Based on Contention Resolution in Optical Burst

Traffic control based on contention resolution process (TCCR) is proposed in this study as a quality of service (QoS) mechanism to offer service level agreement (SLA) for optical burst switch (OBS). QoS of the high and the low priority classes are issued upon their SLA. The first one is defined for real time application as Internet protocol television (IP TV) and voice over Internet protocol (VoIP) while the other is for soft real–time service as Internet protocol remote terminal unit (IP RTU) based on IEC 86070–5–101/104 protocol. A combination of burst aggregation (BA), extra offset time, and fiber delay line (FDL) are utilized in TCCR to offer absolute service differentiation QoS to the high priority class. The experiments show TCCR can offer the high priority class of its satisfied SLA for both blocking probability and delay. It also relatively improves the performances of the low priority class bounded in its SLA because TCCR does not force to drop this class. The performances of TCCR are compared with the other techniques such as no class isolation and bandwidth allocation processes. The comparisons show TCCR gives the best solution of the defined SLA which enhances OBS performances and properly differentiates class of services.

OCL FORMAL SPECIFICATION BASED METRICS AS A MEASURE OF COMPLEXITY AND FAULT-PRONENESS

Formal specification of UML models in OCL is essential to improve software quality. Owing to the use of OCL in precise model specification, its application has been looked in different perspectives such as early measurement of module complexity. Moreover, when UML class diagrams are complemented with OCL, the metrics collected from OCL specification can serve as an indicator of fault-prone components. In the proposed approach an empirical study has been conducted on five soft real time case study applications. In this paper, existing metrics which are applicable to OCL expression are validated using module complexity. Moreover, a new metrics suite, which can be extracted from OCL expressions, has been devoted to quantify module complexity. The proposed metrics suite can be directly extracted from OCL expressions. Relative weight has been assigned to each metric which is selected for the proposed study, based on its importance in fault-prone components identification. The study shows that an analysis on OCL formal specification based metrics is effective in identifying fault-prone components of the system. Furthermore, it helps to distribute efforts required for software development and testing activities.

Energy Efficient Task Scheduling and Data Allocation Strategy in Heterogeneous Environment with Real Time Constraints

paper, we concentrate on the problem of high Energy consumption in heterogeneous environment regarding data allocation scheme in distributed database and task scheduling policies in real-time system. We will focus on soft real time system application having if any deadline is missed then time penalty is occurred. Here we will combine both shared memory as well as in-memory database concepts in heterogeneous database environment. Basically in our paper we will concentrate on try to perform task within deadline having various type of databases responsible to store data. An important problem is how to assign processors to real-time application tasks, obvious here basically concentrate on real time scheduling strategy. As per studied that algorithm concentrate on EDF algorithm having preemptive nature. When higher priority transaction currently going to allocate processor and execute that transaction but another transaction is most needful to execute primary so using preemptive scheduling policy try to overcome that type of problem. Here global index is maintain into the local cache that is responsible to fast search particular server where that result is available and try to give response within time constraint and the total system energy consumption can be minimized. In this paper concentrate on replicas of databases due to this when any specific system crash then able to restore that database. KeywordsSystem, Shared Memory DB, In-Memory DB,

An Efficient Non-Preemptive Algorithm for Soft Real-Time Systems using Domain ClusterGroup EDF

this paper a new non-preemptive domain clustering scheduling algorithm for soft real time application is proposed. The main aim of this algorithm is to achieve high deadline meeting ratio of the group Earliest Deadline First (gEDF) algorithm by maintaining the excellent performance during normal load. An efficient non-preemptive algorithm called Domain Cluster - group EDF (DC-gEDF) is proposed for real time systems which makes clustering the task according to the domain specification with their deadlines and schedules the tasks within a group. The results are analysed and compared for the metric deadline meeting ratio of gEDF and DC-gEDF under different deadline acceptable values. It shows an improvement in the deadline meeting ratio for the proposed DC-g-EDF algorithm. General Terms Real time scheduling

SOFT REAL TIME AUCTION SCHEME FOR TASK ALLOCATION IN WIRELESS SENSOR NETWORKS

In resource constrained wireless sensor networks, one of the fundamental challenges is to achieve a fair energy balance among nodes to maximize the overall network lifetime. Auction based schemes are one of the best method to maximize the network Lifetime. Existing Real Time Effective Auction (RTE-A), task allocation algorithm based on Auction method is not efficient in terms of evaluating the best bid value. As it solely based on real time auction method where successor of the current task may not be the best because, in the RTE-A the auction process is stopped as soon as auctioneer get bid value higher than threshold value. Real Time Effective Auction (RTE-A) algorithm is too stringent with respect to time constraints. But many applications may require resource allocation process which is flexible w.r.t time constraints. In our proposed algorithm a soft real time auction approach is used. Where winner of the auction process is not decided as soon as auctioneers get the bid value higher than threshold value But Auctioneer will have a particular time slot, which is based on application requirement. The auctioneer will decide winner at the end of the specific time slot based on maximum bid value. . In our proposed algorithm (SRT-A), we also improve real time task allocation approach by using wait time at the bidder side. The wait time method, tries to get the best bid value by allowing the node with highest bid value to bid earlier than other nodes. Proposed algorithm gives much better bid value in less time in real time application compare to RTE-A algorithm.

Soft real-time EPICS extensions for fast control: A case study applied to a TCV equilibrium algorithm

For new control systems development, ITER distributes CODAC Core System that is a software package based on Linux RedHat, and includes EPICS (Experimental Physics and Industrial Control System) as software control system solution. EPICS technology is being widely used for implementing control systems in research experiments and it is a very well tested technology, but presents important lacks to meet fast control requirements. To manage and process massive amounts of acquired data, EPICS requires additional functions such as: data block oriented transmissions, links with speed-optimized data buffers and synchronization mechanisms not based on system interruptions. This EPICS limitation turned out clearly during the development of the Fast Plant System Controller Prototype for ITER based on PXIe platform.In this work, we present a solution that, on the one hand, is completely compatible and based on EPCIS technology, and on the other hand, extends EPICS technology for implementing high performance fast control systems with soft-real time characteristics. This development includes components such as: data acquisition, processing, monitoring, data archiving, and data streaming (via network and shared memory). Additionally, it is important to remark that this system is compatible with multiple Graphics Processing Units (GPUs) and is able to integrate MatLab code through MatLab engine connections. It preserves EPICS modularity, enabling system modification or extension with a simple change of configuration, and finally it enables parallelization based on data distribution to different processing components.With the objective of illustrating the presented solution in an actual tokamak application, we have implemented fundamental tokamak equilibrium quantities such as plasma position, Shafranov shift or internal inductance. The algorithms have been parallelized and implemented for its execution on CPU, GPUs and Matlab, and have been tested using actual magnetic data from the TCV tokamak fast control system.

From Offline toward Real Time: A Hybrid Systems Model Checking and CPS Codesign Approach for Medical Device Plug-and-Play Collaborations

Hybrid systems model checking is a great success in guaranteeing the safety of computerized control cyber-physical systems (CPS). However, when applying hybrid systems model checking to Medical Device Plug-and-Play (MDPnP) CPS, we encounter two challenges due to the complexity of human body: 1) there are no good offline differential equation-based models for many human body parameters; 2) the complexity of human body can result in many variables, complicating the system model. In an attempt to address the challenges, we propose to alter the traditional approach of offline hybrid systems model checking of time-unbounded (i.e., infinite horizon, a.k.a., long run) future behavior to online hybrid systems model checking of time-bounded (i.e., finite horizon, a.k.a., short run) future behavior. According to this proposal, online model checking runs as a real-time task to prevent faults. To meet the real-time requirements, certain design patterns must be followed, which brings up the codesign issue. We propose two sets of system codesign patterns for hard real time and soft real time, respectively. To evaluate our proposals, a case study on laser tracheotomy MDPnP is carried out. The study shows the necessity of online model checking. Furthermore, test results based on real-world human subject trace show the feasibility and effectiveness of our proposed codesign.

An Energy-Aware Routing Protocol for Query-Based Applications in Wireless Sensor Networks

Wireless sensor network (WSN) typically has energy consumption restriction. Designing energy-aware routing protocol can significantly reduce energy consumption in WSNs. Energy-aware routing protocols can be classified into two categories, energy savers and energy balancers. Energy saving protocols are used to minimize the overall energy consumed by a WSN, while energy balancing protocols attempt to efficiently distribute the consumption of energy throughout the network. In general terms, energy saving protocols are not necessarily good at balancing energy consumption and energy balancing protocols are not always good at reducing energy consumption. In this paper, we propose an energy-aware routing protocol (ERP) for query-based applications in WSNs, which offers a good trade-off between traditional energy balancing and energy saving objectives and supports a soft real time packet delivery. This is achieved by means of fuzzy sets and learning automata techniques along with zonal broadcasting to decrease total energy consumption.

RTH-RSS Mac: Path loss exponent estimation with received signal strengthlocalisation mechanismin Wireless Sensor Networks

Nowadays , Wireless Sensor Networks (WSNs) succed in domain of technology trends; new require’sare continuously have more complex challenging, such as the real time location. The MAC layer plays a crucial role in these networks; it controls the communication module and manages the medium sharing. In this work, we integrate the received signal strength path-loss exponent estimation (RSS PLE) based on location technique in Real Time Hybrid MAC (RTHMAC) protocol in goal to minimize the delay phase’s and get more life time node’s. It combinesalso the advantages of both TDMA and FDMA in order to give a soft real time communication for WSN.

Reliability aware dynamic voltage and frequency scaling for improved microprocessor lifetime

Dynamic voltage and frequency scaling (DVFS) is heavily used for power management in real-time environments. Although the schemes leveraging DVFS provide significant power reduction, adverse effects on chip reliability are possible. Alternate increase and decrease in operating voltage and frequency leads to thermal cycling. Increasing transistor packing density leads to a larger range of possible operating temperatures, exacerbating the thermal cycling problem. Also, the chip reliability quantification process does not include and represent the effects of small scale thermal cycles. A good number of in-field chip failures are attributed to the consequences of these. Thus, it is imperative to include their effects into the processor voltage and frequency selection process. Our work develops an integrated processor thermal and performance management technique centered on novel polynomial time scheduling algorithms that lead to lowering of thermal cycles in soft real time environments. Our technique leverages application awareness and runtime monitoring for improving chip lifetime, while achieving considerable energy savings. We show that a significant reduction in thermal cycles and peaks is possible, leading to longer chip life expectations.

Mobile Cloud Middleware

Mobile Cloud Computing (MCC) is arising as a prominent research area that is seeking to bring the massive advantages of the cloud to the constrained smartphones. Mobile devices are looking towards cloud-aware techniques, driven by their growing interest to provide ubiquitous PC-like functionality to mobile users. These functionalities mainly target at increasing storage and computational capabilities. Smartphones may integrate those functionalities from different cloud levels, in a service oriented manner within the mobile applications, so that a mobile task can be delegated by direct invocation of a service. However, developing these kind of mobile cloud applications requires to integrate and consider multiple aspects of the clouds, such as resource-intensive processing, programmatically provisioning of resources (Web APIs) and cloud intercommunication. To overcome these issues, we have developed a Mobile Cloud Middleware (MCM) framework, which addresses the issues of interoperability across multiple clouds, asynchronous delegation of mobile tasks and dynamic allocation of cloud infrastructure. MCM also fosters the integration and orchestration of mobile tasks delegated with minimal data transfer. A prototype of MCM is developed and several applications are demonstrated in different domains. To verify the scalability of MCM, load tests are also performed on the hybrid cloud resources. The detailed performance analysis of the middleware framework shows that MCM improves the quality of service for mobiles and helps in maintaining soft-real time responses for mobile cloud applications.