Comparing two-phase locking and optimistic concurrency control protocols in multiprocessor real-time databases

Previous studies (Haritsa et al., 1990) have shown that optimistic concurrency control (OCC) generally performs better than lock-based protocols in disk-based real-time database systems (RTDBS). We compare the two concurrency control protocols in both disk-based and memory-resident multiprocessor RTDBS. Based on their performance characteristics, a new lock-based protocol, called two phase locking-lock write all (2PL-LW), is proposed. The results of our performance evaluation experiments show that different characteristics of the two environments indeed have great impact on the protocols' performance. We identify such system characteristics and show that our new lock-based protocols, 2PL-LW, is better than OCC in meeting transaction deadlines in both disk-based and memory-resident RTDBS.published_or_final_versio

Research on Parallel Real-time Scheduling Algorithm of Hybrid Parameter Tasks on Multi-core Platform

Abstract: Nowadays, multi-core processors are becoming main stream in computer market due to their high performance, low cost and less power consumption characteristics. However, multi-core processors give rise to new problems when they are applied to real-time system. Little attention has been focused on tasks' DMR(deadline miss rate) by using previous multi-core real time scheduling algorithms under the overload condition. As a result, the domino effect will happen because of many tasks failing to meet their deadlines. Meanwhile, the system performance is leaded to drop sharply. In order to alleviate this problem, this paper proposes a new multi-core real time scheduling algorithm which extends the Pfair scheduling method using tasks' hybrid parameters. In addition, the paper will also discuss the tasks' allocation method which would decrease the switch cost. Experimental results for schedules demonstrate that our scheme enables the real time tasks to be scheduled more efficiently on multi-core platform by adopting hybrid parameter priority. Furthermore, the system performance has gained the robust characteristic, because more real time tasks can meet their deadline under the overload condition

Characteristics of agent-based hierarchical diff-EDF schedulability over heterogeneous real-time Packet networks

Packet networks are currently enabling the integration of heterogeneous traffic with a wide range of characteristics that extend from video traffic with stringent QoS requirements to best-effort traffic requiring no guarantees. QoS guarantees can be provided in packet networks by the use of proper packet scheduling algorithms. In this paper, we propose a new priority assignment scheduling algorithm, Hierarchical Diff-EDF, which can meet the real-time needs while continuing to provide best effort service over heterogeneous network traffic environment. The Hierarchical Diff-EDF service meets the flow miss rate requirements through the combination of single step hierarchal scheduling for the different network flows and the admission control mechanism that detects the overload conditions to adjust packets' priorities. To examine the proposed scheduler, we introduced an attempt to provide an exact analytical solution. The attempt showed that the solution was apparently very complicated due to the high interdependences between the system queues' service. Hence, the use of simulation seems inevitable. A multi-agent simulation that takes the inspiration from object-oriented programming is adopted. The simulation itself is aimed to the construction of a set of elements which, when fully elaborated, define an agent system specification. When evaluating our proposed scheduler, it was extremely obvious that the Hierarchical Diff-EDF scheduler performs over both of the EDF and Diff-EDF schedulers

Temporal and Contextual Dependencies in Relational Data Modeling

Although a solid theoretical foundation of relational data modeling has existed for decades, critical reassessment from temporal requirements’ perspective reveals shortcomings in its integrity constraints. We identify the need for this work by discussing how existing relational databases fail to ensure correctness of data when the data to be stored is time sensitive. The analysis presented in this work becomes particularly important in present times where, because of relational databases’ inadequacy to cater to all the requirements, new forms of database systems such as temporal databases, active databases, real time databases, and NoSQL (non-relational) databases have been introduced. In relational databases, temporal requirements have been dealt with either at application level using scripts or through manual assistance, but no attempts have been made to address them at design level. These requirements are the ones that need changing metadata as the time progresses, which remains unsupported by Relational Database Management System (RDBMS) to date. Starting with shortcomings of data, entity, and referential integrity in relational data modeling, we propose a new form of integrity that works at a more detailed level of granularity. We also present several important concepts including temporal dependency, contextual dependency, and cell level integrity. We then introduce cellular-constraints to implement the proposed integrity and dependencies, and also how they can be incorporated into the relational data model to enable RDBMS to handle temporal requirements in future. Overall, we provide a formal description to address the temporal requirements’ problem in relational data model, and design a framework for solving this problem. We have supplemented our proposition using examples, experiments and results

Transient force atomic force microscopy: systems approaches to emerging applications

In existing dynamic mode operation of Atomic Force Microscopes (AFMs) steady-state signals like amplitude and phase are used for detection and imaging of material. Due to the high quality factor of the cantilever probe the corresponding methods are inherently slow. In this dissertation, a novel methodology for fast interrogation of material that exploits the transient part of the cantilever motion is developed. This method effectively addresses the perceived fundamental limitation on bandwidth due to high quality factors. It is particularly suited for the detection of small time scale tip-sample interactions. Analysis and experiments show that the method results in significant increase in bandwidth and resolution as compared to the steady-state-based methods;In atomic force microscopy, bandwidth or resolution can be affected by active quality factor (Q) control. However, in existing methods the trade off between resolution and bandwidth remains inherent. Observer based Q control method provides greater flexibility in managing the tradeoff between resolution and bandwidth during imaging. It also facilitates theoretical analysis lacking in existing methods;In this dissertation we develop a method for exact constructive controllability of quantum-mechanical systems. The method has three steps, first a path from the initial state to the final state is determined and intermediate points chosen such that any two consecutive points are close, next small sinusoidal control signals are used to drive the system between the points, and finally quantum measurement technique is used to exactly achieve the desired state. The methodology is demonstrated for the control of spin-half particles in a Stern-Gerlach setting;In this dissertation, a novel closed-loop real-time scheduling algorithm is developed based on dynamic estimation of execution time of tasks based on both deadline miss ratio and task rejection ratio in the system. This approach is highly preferable for firm/soft real-time systems since it provides a firm performance guarantee in terms of high guarantee ratio. Proportional-integral controller and H-infinity controller are designed for closed loop scheduling. Simulation studies showed that closed-loop dynamic scheduling offers a better performance over the openloop scheduling under all the practical conditions

Multiclass Query Scheduling in Real-Time Database Systems

In recent years, a demand for real-time systems that can manipulate large amounts of shared data has led to the emer-gence of real-time database systems (RTDBS) as a research area. This paper focuses on the problem of scheduling queries in RTDBSs. We introduce and evaluate a new algorithm called Priority Adaptation Query Resource Scheduling (PAQRS) for handling both single class and multiclass query workloads. The performance objective of the algorithm is to minimize the number of missed deadlines, while at the same time ensuring that any deadline misses are scattered across the different classes according to an administratively-defined miss distribution. This objective is achieved by dynamically adapting the system’s admission, mem-ory allocation, and priority assignment policies according to its current resource configuration and workload characteristics. A series of experiments confirms that PAQRS is very effective for real-time query scheduling

An adaptive load sensing priority assignment protocol for distributed real-time database systems.

Transaction processing in a distributed real time database system (DRTDBS) is coordinated by a concurrency control protocol (CCP). The performance of a CCP is affected by the load condition of a transaction processing system. For example, the performance of the Adaptive Speculative Locking (ASL) protocol degrades in high load conditions of the system. Priority protocols help a CCP by prioritizing transactions. The performance of the priority protocols is also affected by system load conditions, but they can be optimized by dynamically switching between priority protocols at run time when the system load changes. The objective of this research is to develop a protocol, Adaptive Priority Assignment protocol (APAP), which changes the priority protocol at run time to improve the performance of a CCP in a DRTDBS. APAP is implemented in a DRTDBS, where ASL is used as the underlying CCP to validate APAP. The performance of APAP was tested under varying system load conditions with various combinations of the database system parameters. Under the scenarios tested, APAP performed better than other priority protocols and demonstrated that dynamic selection of priority protocols during run time is an effective way to improve the performance of a CCP in a DRTDBS. --Leaf ii.The original print copy of this thesis may be available here: http://wizard.unbc.ca/record=b183575

Earliest Deadline Scheduling for Real-Time Database Systems

Earlier studies have observed that in moderately-loaded real-time database systems, using an Earliest Deadline policy to schedule tasks results in the fewest missed deadlines. When the real-time system is overloaded, however, an Earliest Deadline schedule performs worse than most other policies. This is due to Earliest Deadline giving the highest priority to transactions that are close to missing their deadlines. In this paper, we present a new priority assignment algorithm called Adaptive Earliest Deadline (AED), which features a feedback control mechanism that detects overload conditions and modifies transaction priority assignments accordingly. Using a detailed simulation model, we compare the performance of AED with respect to Earliest Deadline and other fixed priority schemes. We also present and evaluate an extension of the AED algorithm called Hierarchical Earliest Deadline (HED), which is designed to handle applications that assign different values to transactions and where the..

Exploiting Soft Computing for Real time performance

The classic approach to the design of real time systems is to determine worst-case scenarios for the system statically and manually and then build the system with sufficient resources to meet deadlines and goals. This approach has worked well for traditional real time systems which operate in relatively simple, well-characterized environments. However the emerging generation of complex, dynamic and uncertain real time application domains accentuates the growing need for flexible, adaptable design approaches for real time systems. With the increasing complexity of real time systems, it is becoming infeasible to build systems with sufficient resources to meet the functional and timing requirements of all application tasks at all times. What is becoming increasingly important in the new paradigm of real time computing is the need to meet deadlines with sufficient system solution quality without having to design the system to support worst case program execution. In this thesis, we explore the possibility of exploiting "soft computing" properties of kernels to meet this objective. The chief characteristic of "soft computations" is the fact that they are able to provide cruder results before they complete, or they may execute for a long time refining an already adequate result. In other words, such computations are able to provide useful/incremental results before fully completing execution. More specifically they provide a trade-off between computation time and algorithm solution quality. This thesis addresses the design issues involved in building a system that exploits the "soft computing" properties of kernels to optimize real time performance. In this context, we make the following contributions. Firstly we build a system prototype of a real time situational assessment scenario. We thereafter identify "soft computations" in the system and characterize the computation time/solution quality trade-off opportunities provided by them using performance profiles. Thirdly, we introduce a method to use performance profile based models at run time to determine the optimal composition of different "soft computations" in order to meet real time deadlines with sufficient system solution quality. We quantify the gains from our method both in terms of functional correctness of the system as well as CPU utilization as compared to conventional real time scheduling techniques. We observe that our dynamic scheduling scheme on an average is able to meet the system goals with 39% more accuracy with no missed deadlines as compared to conventional real time scheduling techniques for various design points that do not support worst case behavior. In addition, our method is able to meet the system objective while being highly utilized. Most importantly, our scheme exploits the soft computing properties of kernels to facilitate the design of the system at less aggressive design points while meeting deadlines and system goals at the same level as conventional real time design methodology. Finally, we perform an experimental study to understand the sensitivity of performance profiles to various input data parameters and identify the potential for online learning of performance profiles