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UBICC, the Ubiquitous Computing and Communication Journal [ISSN 1992-8424], is an international scientific and educational organization dedicated to advancing the arts, sciences, and applications of information technology. With a world-wide membership, UBICC is a leading resource for computing professionals and students working in the various fields of Information Technology, and for interpreting the impact of information technology on society.
Special Issue on Ubiquitous Computing Security Systems APPROACH TO DETERMINING AN EXTERNAL PROBLEM FOR SELF-HEALING Jeongmin Park, Joonhoon Lee, Hyunsang Youn, and Eunseok Lee School of Information and Communication Engineering Sungkyunkwan University Suwon 440-746, South Korea email@example.com, firstname.lastname@example.org, email@example.com, firstname.lastname@example.org ABSTRACT Self-healing is a methodology used for constructing a system that can detect faults and recover itself and returns from an abnormal state to a normal state. Much attention has recently been focused on self-healing ability that recognizes problems arising in a target system. However, if a system wants to provide self-healing functionalities, there are many loads such as target system analysis and system environment analysis for external problem. Thus, this paper proposes using deployment diagram for self-healing approach to determine problem arising in external environment. The UML deployment diagram is widely used for resource specification of a system and generally designed in the system design phase. The approach proposes of 1) analysis for associations between software and hardware; 2) generating a monitor using constraints in deployment diagrams; and 3) adding the monitor to the component after adapting it to the specific software architecture. As proof of the approach, we automatically generate a resource monitor automatically, and used a video conference system. We illustrate how the method detects anomalies using the example. Keywords: External problem, Problem Deternmination, External state 1 INTRODUCTION • Analyzing associations between software and hardware in the UML deployment diagram of a The complexity of the software execution component. environment poses new challenges for software • Generating the resource monitor using constraints developers. When computer systems operate specified by the designer in the diagram. abnormally, detecting and resolving the problem • Adding the monitor to the component after requires much time and effort. Therefore, software adapting the component's structure should adapt without human intervention to achieve a self-healing ability. Self-healing is concerned with Through our approach, resource monitor can be the ability of the system to automatically recover generated automatically using the deployment from faults [1,2]. diagram for a target system. It is useful in Self-healing components have been the subject of implementing the resource monitor for the several studies. For constructing a system that component because it reduces additional work for facilitates self-healing, Shin et al.[3,4,5] propose monitoring the resources. self-healing component architecture. Faults can be Component developers just simply modify parts divided into two types in views of the system: the of the monitor generated automatically for adaptation fault occurred in software and the fault from and can easily add healing strategies to it. For resources such as a cpu usage, a ram usage, and illustrating the approach, we tested our method by bandwidth, etc. adapting a video conference system for evaluation. However, this approach does not focus on faults We can see that the monitor generated by our method arising from resources. The monitor for self-healing worked correctly when a resource problem occurred. in the Healing Layer must be implemented by the The next section of the paper describes related work. developer and it requires additional efforts in the Section 3 presents the approach in more detail. software development process. Section 4 illustrates evaluations for the approach. In this paper, we describe an approach to The paper ends with a summary in Section 5. generate the resource monitor automatically by using a UML Deployment diagram. The approach consists of the following steps: UbiCC Journal – Volume 4 670 Special Issue on Ubiquitous Computing Security Systems 2 RELATED WORK The architecture does not allow detailed mistakes. Only faults that occurred in the In this section, we present a self-healing component can be detected. component architecture [3,4,5] and an Autonomic Failure-Detection algorithm , which is one of the failure detection methods. 2.2. Autonomic Failure-Detection Algorithm Mills et al.  proposed an algorithm that detects 2.1. Layered software architecture for a self- failures automatically. In the approach, objects and healing component devices that need to be observed send a signal to the monitor periodically, similarly to a human’s Each self-healing component consists of a heartbeat. The monitor can manage many healing layer and a service layer.[3,4,5] The components. It determines whether the object or service layer performs tasks requested by another device has a problem by checking the signal over task or component in the system. It also contains time. Let H p represent the period of a signal. The active objects, connectors, and passive objects, maximum time for detecting faults will then also be which are accessed by active objects. The active H p . However, faults can occur at any time during object can execute another active object or a passive object. In contrast, a passive object is the signal period. The average time for detecting called only by an active object. It cannot perform faults is H p / 2 . This algorithm can identify whether independently unless another object calls it. The an object has problems or not in a very short time. connectors transfer messages to or from tasks and However, it has an overhead cost because it requires synchronize them. frequent communication to exchange the signal The healing layer makes a decision that an between the monitor and the objects. object in the service layer of the component becomes sick, the healing process is launched via connectors. It is composed of 6 objects as follows. 3 PROPOSED APPROACH • Component Monitor: This module observes In this paper, we present an improved self- behaviors of each object through messages healing component architecture that can recover from connectors in the service layer. resource problems. We do not focus on inner • Component Reconfiguration Plan problems in this paper because this is covered by Generator: This module produces Shin et al.[3,4,5] The resource in this case could reconfiguration plans for when a fault occurs be independent of the software. The monitor in the service layer. It also has information for measures the state of resources periodically and objects in the service layer. decides whether self-healing policies should be adopted or not. For this, we used a modified “heartbeat” algorithm. The algorithm sends the • Component Repair Plan Generator: This signal to resources. Through this mechanism, the module constructs self-healing strategies for resource monitor can measure values and detect faulty objects. It has recovery plans for each object in the service layer. anomalies. • Component Reconfiguration Executor, 3.1. Architecture for generating resource monitor Component Repair Executor: These modules execute plans generated by the plan The architecture can be divided into an generators. analyzing phase and a generation phase. Figure 1 illustrates the flow of structure. The architecture can be divided into an analyzing phase and a • Component Self-healing Controller: This generation phase. Figure 1 illustrates the flow of module controls the five modules above. structure. This architecture has the following features. The architecture can identify an object • UML Deployment Diagram: This is the input of with faults. the architecture. The diagram is transformed into Healing strategies for each object are an XMI (XML Meta-Interchange)[7,8]. pre-made. UbiCC Journal – Volume 4 671 Special Issue on Ubiquitous Computing Security Systems • XMI Parser: The XMI parser analyzes resource means the duration time until the detection of constraints of and associations with the resource. a fault. It can be also said to be the waiting In the analyzing phase, the outputs are time in the method; initially, its value is 1 monitoring targets and constraints. These outputs second. This value is used as a setting value are parsed in XML format. for experiments and can be changed for any • Monitor Template Generator: The monitor system environment. template generator uses the output of the XMI parser. It generates a monitor template, which Table 1: Constraints List detects device problems or resources selected for Contents Input Unit monitoring. This template is implemented in the CPU 0.0 ~ 1.0 Percent specific language. usage Mem 0.0 ~ 1.0 Percent • Configuring: The monitoring template code usage need to be modified for adaptation. The software Heartbeat 0.1 ~ 1.0 Second developer configures it for the structure of User defined software. Bandwidth minimum KB/s bandwidth • Resource Monitor: The resource monitor User defined generated by the approach can be adapted to the Method connection software directly. type Duration time Duration for detecting Second fault • Step2 - Analyzing diagram: At first, the node (for example, client, server etc) was identified in the system. Next, constraints for resources, such as the constraints of cpu, Memory, Bandwidth and Heartbeat rate, were identified. The Parsing Engine parses XMI information (Fig. 4.) and generates XML about the two types. Figure 1: Architecture for generating resource monitor 3.2. Process of approach We present the process composed of 4 steps in this section (Fig. 2). • Step1 - Specifying the system using a UML deployment diagram: Initially, the software developer creates a deployment diagram (Fig. 3). The deployment diagram is a diagram which represents a static aspect of the system in the UML design model and illustrates associations among components. Constraints proposed within the method are shown in Figure2: Process of approach (4-steps) Table 1 Method means linking techniques of network or physical devices and using them • Step3 - Generating monitor template: In this for detecting abnormal terminations. Duration step, the template for an executable resource UbiCC Journal – Volume 4 672 Special Issue on Ubiquitous Computing Security Systems monitor was generated by using the information analyzed in the previous step. The Template 3.3. Problem detection algorithm Generator (TG) performs the generation of a monitor by analyzing the XML generated by In this section, we describe the parts that were the Parsing Engine. It also generates fault adapted to the autonomic fault-detection algorithm processing and anomaly detection routines for relate to our approach (Fig. 5). The resource monitor each constraint. (Fig. 2) in the self-healing layer judges the state of the • system as abnormal if a reply is sent to the devices or resources and does not return in the period. It was also regarded as abnormal if the values of the resource violated a constraint. In this context, a self- healing layer should construct a reconfiguration plan and perform it. Unlike related works, Lmax and Lavg are 1.5 times longer than before because the monitor sends the signal first. The monitor determines that a resource is still in the normal state if a fault has occurred just after replying to the monitor. At this time, it sends a signal that tells it to Figure3: Deployment diagram example cycle to a new resource. However, the resource is actually in fault, and a cycle is wasted because the resource is already in trouble. Therefore, our approach takes more time to detect faults than related work. Figure5: Error detection algorithm 3.4. Self-healing components including resource monitor Resource monitoring is illustrated in Fig. 6. The device and self-healing component Figure4: XMI Information and constraints model architecture featured resource monitoring. derived from a deployment diagram Devices and the modified architecture available to resources monitoring the self-healing • Step4 - Composing monitor: In this step, a component architecture were designed by E. Shin developer modifies the resource monitor [2, 3]. Resource monitoring is illustrated in Fig. 6. according to the software environment. The fault processing handler or guidelines are The device and self-healing component actually implemented in the monitor template architecture featured resource monitoring. generation level by the approach. It also Devices and the modified architecture available performs customization regarding parts needed to resources monitoring the self-healing and parts modified. Afterwards, a resource component architecture were designed by E. Shin monitor is added to the self-healing layer or [2, 3]. component. UbiCC Journal – Volume 4 673 Special Issue on Ubiquitous Computing Security Systems In this paper, we present an improved self- healing component architecture that can recover resource problems. We do not focus on inner problems in this paper because this is covered by Shin et al.[3,4,5] The resource in this case could be independent of the software. The monitor measures the state of resources periodically and decides whether self-healing policies should be adopted or not. For this, we used a modified “heartbeat” algorithm. The algorithm sends the signal to resources. Through this mechanism, the resource monitor can measure values and detect anomalies. To evaluate the algorithm, we expressed the Figure6: Proposed Self-healing component basic design of a video-based conference system. architecture The purpose of this system was to successfully conduct a video-based conference. During the Six objects used for healing referred meeting, the client should not be interrupted by components and three objects used for detecting external problems of the software. In this paper, resources and reorganizing is added in this the purpose was to check whether the client architecture. The added objects are divided into detected errors that arose from the software's three parts. : External Resource Monitor, external problems after automating the resource External Resource Reconfiguration Plan monitor and applying it to the client in the video- Generator, and External Resource based conference system by the approach Reconfiguration Executor. External Resource Monitor checks the status of external devices and resources. External Resource Reconfiguration Plan Generator makes organizational plans for service levels in accordance with external situations. External Resource Reconfiguration Executor executes the plans. The purpose of the External Resource Figure7: Parsing Engine Prototype Reconfiguration Plan Generator is to make plans that prevent other well-operating objects from being affected by other resources by isolating objects that are easily influenced by resources, similar to the organization of the component plans. Self-healing Controller that controls objects in the self-healing layer governs the resource reconfiguration executor to perform a reconfiguration of the service layer. When it Figure8: Template Generator Prototype comes to external errors, it performs in the same way and allows anomalies of the service layer by 4.1. Environments minimizing resources. To evaluate this approach, we implemented clients of a video conferencing system based on .NET Framework 2.0. We used C# with the 4 Implementation and Evaluation implements in MS Windows XP. We used Borland Together for UML modeling. The server was UbiCC Journal – Volume 4 674 Special Issue on Ubiquitous Computing Security Systems implemented by Java2 SDK 1.4. The client the client, and a routine that prints the error time in a additionally used DirectShow.NET for the video resource monitor in pursuit of the accuracy of the device. A deployment analyzer and resource monitor Failure-Detection Latency evaluation. The detection template were also implemented in C#. Fig. 3 results for various constraints are listed in Table 2. illustrated the deployment diagram that we used. Fig. The error detection time, which was estimated for the 7 and Fig. 8 illustrate the Parsing Engine prototype CPU for 10 times, is shown in Fig. 10. and Template Generator. Table 2: Experimental results of the monitoring 4.2. Normal case Success of Check list Constraints Resource monitor continues to monitor the detection resource unless resource performs its work CPU Max 80% Success without any anomalies. usage Memory usage Max 70% Success 4.3. Abnormal case Monitor detects an abnormal state when the Bandwidth usage Min 50KB/s Success measured value was over the normal range or the connection with the other resources was accidentally Abnormal Network terminated. Figure 9 illustrates the case when the network Success connection CPU usage was in excess of 80%. In this paper, we determination did not focus on self-healing strategies. Therefore, strategies for healing the faulty state were generated by the administrator. Figure 10: Error detection time of resource monitor As a result of the evaluation, the resource monitor detected the four items that constraints Figure 9: Detection of anomalies of CPU by monitor are set up. Even though there were differences in the average fault detection time, we were able to verify that the resource monitor could detect it 4.4. Objective of evaluation and the results within the maximum fault detection time. The purpose of the evaluation is to determine whether the approach recognizes error situations or 5 CONCLUSION not within a designated time in applied purpose This paper proposed an approach to reduce the systems and to compare applied target systems with efforts of a self-healing developer and offered a not applied to the system, if errors occur in the software architecture that detects the resources resources. We used programs such as the available. The produce of resource monitors can benchmarking program and forced server be automated by using the deployment diagram. determination in the case of extreme situations in the The advantages are listed below. system. Additionally, we added a routine that immediately reports the time when errors occur in UbiCC Journal – Volume 4 675 Special Issue on Ubiquitous Computing Security Systems • The resource monitor production is  Micheal E.Shin, Jung Hoon An, “Self- reconfiguration in self-healing systems”, automated Proceedings of the 3th IEEE international • A strategy is in place in the case of faults Workshop on EASE’06, pp.106-116 (2006). in resources.  K. Mills, S. Rose, S. Quirolgico, M. Britton, C. Tan, "An autonomic failure-detection Until now, developers have to do more effort algorithm", ACM SIGSOFT Software Engineering Notes, Vol. 29, Issue 1, pp. 79- to implement the monitor which checks resources 83(2004). for the software. However, in this study, we  G. Booch, J. Rumbaugh, I. Jacobson, "The confirmed that we could make resource monitors Unified Modeling Language User Guide", automatically that can include a self-healing Addison Wesley, pp.100-150 (1999). component by a deployment diagram. To  XMI Online Document, http://www.omg.org/xml evaluate these, we arranged a prototype component and confirmed whether the detection monitor operated correctly when an abnormal situation occurred. However, we could not overcome a high overhead since signals must be exchanged frequently if errors are to be detected. To solve this problem, a study that investigates self- regulating cycles of exchanging signals between monitors is needed. The study of automation in self-healing strategies for recovering from faulty states remains future work. 6 ACKNOWLEDGEMENT This work was supported by the Korea Science and Engineering Foundation (KOSEF) grant funded by the Korea government (MEST) (No. 2009-0077453) and a result of Faculty Research Fund (2008) of Sungkyunkwan University. Corresponding author: Eunseok Lee. 7 REFERENCES  B.Topol, D.Ogle, D. Pierson, J. Thoensen, J. Sweitzer, M. Chow, M. A. Hoff-mann, P. Durham, R. Telford, S. Sheth, T. Studwell, “Automating problem determination: A first step toward self-healing computing system”, IBM white paper (2003).  D. Ghosh, R. Sharman, H. R. Rao, S. Upadhyaya, "Self-healing - survey and synthesis", Decision Support Systems in Emerging Economies, Vol. 42, Issue 4, pp. 2164-2185 (2007).  Michael E. Shin, "Self-healing component in robust software architecture for concurrent and distributed systems", Science of Computer Programming, Vol. 57, No. 1, pp. 27-44 (2005).  Michael E. Shin and Jung Hoon An, "Self- Reconfiguration in Self-Healing Systems", Proceedings of the Third IEEE International Workshop on EASE'06, pp 89-98 (2006). UbiCC Journal – Volume 4 676
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