Tolga Ayav

Solving the Course Scheduling Problem Using Simulated Annealing

This paper tackles the NP-complete problem of academic class scheduling (or timetabling). The aim is to find a feasible timetable for the department of computer engineering in ¿zmir Institute of Technology. The approach focuses on simulated annealing. We compare the performance of various neighborhood searching algorithms based on so-called simple search, swapping, simple search-swapping and their combinations, taking into account the execution times and the final costs. The most satisfactory timetable is achieved with the combination of all these three algorithms. The results highlight the efficacy of the proposed scheme.

A review of cloud deployment models for e-learning systems

With the significant growth in the cloud-based systems, many industries give their attention to cloud computing solutions. E-learning is a promising application area since its typical requirements such as dynamically allocation of computation and storage resources, coincide well with cloud characteristics. This paper presents some possible cloud solutions in e-learning environments by emphasizing its pros and cons. It is of paramount importance to choose the most suitable cloud model for an e-learning application or an educational organization in terms of scalability, portability and security. We distinguish various deployment alternatives of cloud computing and discuss their benefits against typical e-learning requirements.

Adaptive RTP Rate Control Method

In this paper, we present an adaptive method for maximizing network bandwidth utilization for the real-time applications. RTP protocol is chosen as the transport protocol and the network utilization is provided by increasing and decreasing the transmission rate of the RTP traffic. Our method employs a PID controller that keeps the RTP packet loss fraction at a predefined reference point. Packet loss fraction parameter is gathered from the RTCP receiver reports and fed into the PID controller that controls the transmission rate of the RTP traffic. Simulations are performed to demonstrate the effectiveness of the method under a bottleneck network configuration with background UDP traffic competing against the RTP traffic for the available bandwidth.

A Performance and Profit Oriented Data Replication Strategy for Cloud Systems

In todays world, tenants of cloud systems expect timely responses to queries that process ever-increasing sizes of data. However, most cloud providers offer their services without any performance guarantees to their tenants. In this paper we propose a data replication strategy that aims to satisfy performance guarantees for the tenant while ensuring profitability of the cloud provider. Our strategy estimates the response time of the queries, as well as the expenditures that affect the profitability of the cloud provider. The decision of whether to perform replication is determined by the fulfillment of these two criteria. Validity of the proposed strategy is provided by means of a simulation study.

Identifying critical architectural components with spectral analysis of fault trees

Graphical abstractDisplay Omitted HighlightsSpectral (Fourier) analysis is applied to identify the critical components of hardware/software system architecture.A new sensitivity metric, namely spectral sensitivity, is proposed.It is demonstrated that spectral sensitivity outperforms the existing metrics in particular cases. We increasingly rely on software-intensive embedded systems. Increasing size and complexity of these hardware/software systems makes it necessary to evaluate reliability at the system architecture level. One aspect of this evaluation is sensitivity analysis, which aims at identifying critical components of the architecture. These are the components of which unreliability contributes the most to the unreliability of the system. In this paper, we propose a novel approach for sensitivity analysis based on spectral analysis of fault trees. We show that measures obtained with our approach are both consistent and complementary with respect to the recognized metrics in the literature.

Towards Test Case Generation for Synthesizable VHDL Programs Using Model Checker

VHDL programs are often tested by means of simulations, relying on test benches written intuitively. In this paper, we propose a formal approach to construct test benches from system specification. To consider the real-time properties of VHDL programs, we first transform them to timed automata and then perform model checking against the properties designated from the specification. Counterexamples returned from the model checker serve as a basis of test cases, i.e. they are used to form a test bench. The approach is demonstrated and complemented by a simple case study.

Feedback control static scheduling for real-time distributed embedded systems

This paper presents an implementation of feedback control strategy on distributed static scheduling. The static schedule is created taking into account the average execution times of the tasks. Feedback control algorithm handles the unestimated dynamic behaviors in the system and keeps the performance at a desired level. The approach of feedback control supporting static scheduling yields more flexible scheduling, low scheduling overhead and better resource utilization while preserving the realtime constraints.

Ensuring performance and provider profit through data replication in cloud systems

Cloud computing is a relatively recent computing paradigm that is often the answer for dealing with large amounts of data. Tenants expect the cloud providers to keep supplying an agreed upon quality of service, while cloud providers aim to increase profits as it is a key ingredient of any economic enterprise. In this paper, we propose a data replication strategy for cloud systems that satisfies the response time objective for executing queries while simultaneously enables the provider to return a profit from each execution. The proposed strategy estimates the response time of the queries and performs data replication in a way that the execution of any particular query is still estimated to be profitable for the provider. We show with simulations that how the proposed strategy fulfills these two criteria.

Full-Exact Approach for Frequent Itemset Hiding

This paper proposes a novel exact approach that relies on integer programming for association rule hiding. A large panorama of solutions exists for the complex problem of itemset hiding: from practical heuristic approaches to more accurate exact approaches. Exact approaches provide better solutions while suffering from the lack of performance and existing exact approaches still augment their methods with heuristics to make the problem solvable. In this case, the solution may not be optimum. This work presents a full-exact method, without any need for heuristics. Extensive tests are conducted on 10 real datasets to analyze distance and information loss performances of the algorithm in comparison to a former similar algorithm. Since the approach provides the optimum solution to the problem, it should be considered as a reference method.

Prioritizing MCDC test cases by spectral analysis of Boolean functions

Test case prioritization aims at scheduling test cases in an order that improves some performance goal. One performance goal is a measure of how quickly faults are detected. Such prioritization can be performed by exploiting the fault exposing potential (FEP) parameters associated to the test cases. The FEP is usually approximated by mutation analysis under certain fault assumptions. Although this technique is effective, it could be relatively expensive compared to the other prioritization techniques. This study proposes a cost‐effective FEP approximation for prioritizing modified condition decision coverage (MCDC) test cases. A strict negative correlation between the FEP of an MCDC test case and the influence value of the associated input condition allows to order the test cases easily without the need of an extensive mutation analysis. The method is entirely based on mathematics and it provides useful insight into how spectral analysis of Boolean functions can benefit software testing.