ايمن حسن رشيد العوادي

Data center networks (DCNs) act as critical infrastructures for emerging technologies. In general, a DCN involves a multi-rooted tree with various shortest paths of equal length from end to end. The DCN fabric must be maintained and monitored to guarantee high availability and better QoS. Traditional traffic engineering (TE) methods frequently reroute large flows based on the shortest and least-congested paths to maintain high service availability. This procedure results in a weak link utilization with frequent packet reordering. Moreover, DCN link failures are typical problems. State-of-the-art approaches address such challenges by modifying the network components (switches or hosts) to discover and avoid broken connections. This study proposes Oddlab (Odds labels), a novel deployable TE method to guarantee the QoS of multi-rooted data center (DC) traffic in symmetric and asymmetric modes. Oddlab creatively builds a heuristic model for efficient flow scheduling and faulty link detection by exclusively using the gathered statistics from the DCN data plane, such as residual bandwidth and the number of installed elephant flows. Besides, the proposed method is implemented in an SDN-based DCN without altering the network components. Our findings indicate that Oddlab can minimize the flow completion time, maximize bisection bandwidth, improve network utilization, and recognize faulty links with sufficient accuracy to improve DC productivity.

Today’s data centers act as the primary infrastructure for emerging technologies. QoS imposes requirements for more attentive techniques that can deal with different characteristics of traffic classes and patterns. In this context, network flows can be classified into large and long-lived flows called elephant flows and mice flows, which are small and short-lived flows. According to the characteristics of the emerging technologies, e.g., IoT and Big Data, mice flows are dominant; Hence, it is crucial to improve Flow Completion Time (FCT) for such delay-sensitive flows. This paper presents Sieve, a new distributed Software Defined Networks (SDN) based framework. Sieve initially schedules a portion of the flows based on the available bandwidth despite their classes. We propose a distributed sampling technique which sends a portion of the packets to the controller. Furthermore, Sieve polls the edge switches periodically to get the network information rather than polls all switches in the network, and it reschedules elephant flows only. Mininet emulator and mathematical analysis have been employed to validate the proposed solution in 4-ary Fat-Tree DCN. Sieve provides less FCT up to around 58% for mice flows and maintains throughput of elephant flows compared to Equal Cost MultiPath (ECMP) and Hedera.

The emerging technologies leveraging Data Center Networks (DCN) and their consequent traffic patterns impose more necessity for improving Quality of Service (QoS). In this paper, we propose Sieve, a new distributed SDN framework that efficiently schedules flows based on the available bandwidth to improve Flow Completion Time (FCT) of mice flows. In addition, we propose a lightweight sampling mechanism to sample a portion of flows. In particular, Sieve schedules the sampled flows, and it reschedules only elephant flows upon threshold hits. Furthermore, our framework allocates a portion of the flows to ECMP, so that the associated overhead can be mitigated in the control plane and ECMP-related packet collisions are fewer as well. Mininet has been used to evaluate the proposed solution, and Sieve provides better FCT up to 50% in comparison to the existing solutions like ECMP and Hedera.

The emergence of large data centers and virtualization needs better and smarter solutions for traffic scheduling and load balancing. Data centers benefit from SDN regarding centralized monitoring and management for traffic routing. In general, the traffic in the data center environment can be classified as elephant and mice flow. Researchers showed that there is a significant amount of data carried over elephant flows; therefore, it should be conserved and maintained thoroughly. In this work, we introduce a stochastic performance evaluation model for estimating blocked rate prediction and risk analysis of the elephant flows for a load balancing data center with fat-tree topology using the SDN paradigm. The general procedure of the evaluation includes the estimation of the distribution of the path available bandwidth, including bandwidth error tolerance. The proposed model relies on Monte Carlo simulation to generate future prediction behavior of the load balancing technique. The achieved results examined with Value at Risk (VaR) along with statistics to percept the complete picture of the load balancing behavior.

Several Traffic Engineering (TE) techniques based on SDN (Software-defined networking) proposed to resolve flow competitions for network resources. However, there is no comprehensive study on the probability distribution of their throughput. Moreover, there is no study on predicting the future of elephant flows. To address these issues, we propose a new stochastic performance evaluation model to estimate the loss rate of two state-of-art flow scheduling algorithms including Equalcost multi-path routing (ECMP), Hedera besides a flow congestion control algorithm which is Data Center TCP (DCTCP). Although these algorithms have theoretical and practical benefits, their effectiveness has not been statistically investigated and analyzed in conserving the elephant flows. Therefore, we conducted extensive experiments on the fat-tree data center network to examine the efficiency of the algorithms under different network circumstances based on Monte Carlo risk analysis. The results show that Hedera is still risky to be used to handle the elephant flows due to its unstable throughput achieved under stochastic network congestion. On the other hand, DCTCP found suffering under high load scenarios. These outcomes might apply to all data center applications, in particular, the applications that demand high stability and productivity.

Many data centers nowadays begin to switch to SDN (Software-Defined Networking), to gain the main features like predictability, centralized management, quality of service and enhanced security. Comparing with traditional networks, SDN provides the ability to separate the control plane from the data plane with variety of protocols and functionalities like OpenFlow. Therefore, SDN reveals new opportunities to build large, complex and scalable networks using various network applications and services. As for network security and forensic aspects, the centralized control plane presented by SDN enhances the process of monitoring and analysis of network traffic to find the potential threats. However, it is so difficult to diagnose the cause of malevolent behaviors in large network with various services, communications, applications and protocols, without systematic model to investigate for the attacks that could happen in the data center. In this paper, we present new insight for the current trends in the aspect of SDN attacks and faults in distributed data centers in addition to the forensic challenges that have not been addressed yet. To diagnose such issues, we proposed an SDN prototype model based on the proven Provenance Verification Point (PVP) and expanded it to work in widely distributed data centers. The proposed prototype deployed as a centralized forensic middlebox working on collecting information and logs from the control and infrastructure layer of the SDN topology to find the root cause of the malicious attacks.

ضمن نشاطات قسم الحاسبات في كلية التربية وبهدف تعزيز الجانب التطبيقي والعملي لدى طلبات كليتنا في المرحلة الرابعة لعلوم الحاسبات وتهيئتهم للواقع الفعلي في سوق العمل التقني، اقام المدرس ايمن حسن العوادي ورشة عمل يوم الاثنين 21/11/2022 بالتعاون مع فريق قسم الشبكات (المهندس حسين عبد علي والمهندس علي عبد الجبار) في مركز البحث والتأهيل المعلوماتي حول أدوات وتقنيات الميدان العملي لشبكات الحاسوب تعرف من خلالها الطلبة عملياً على أنواع الكابلات المستخدمة في الشبكات منها الضوئية والنحاسية وكيفية التعامل معها من حيث الربط واللحام.

اقام قسم علوم الحاسوب في كلية التربية المختلطة بجامعة الكوفة ضمن سلسلة نشاطات القسم حلقة نقاشية بعنوان "الذكاء الاصطناعي وتحديات التعليم والبحث العلمي" قدم المحاضرة الدكتور ايمن حسن العوادي، وضح فيها الاتجاهات الحديثة في تطبيقات الذكاء الاصطناعي المنتشرة حالياً خصوصاً المُحوّل التوليديّ المُدرَّب مُسبقًا للدردشة (ChatGPT) الذي أطلقته شركة OepnAI والمميزات التي يقدمها في مجال التعليم والبحث العلمي من حيث تعزيز الكفاءة وتطوير مهارات حل المشاكل واقتراح طرق جديدة ومطورة، تطرق المحاضر أيضاً الى المشاكل والتحديثات التي ستواجه الباحثين والتدريسيين في المستقبل القريب بوجود هذه التطبيقات منها تقليل التواصل البشري وانعدام التفكير النقدي والابداعي، وتوصلت المحاضرة الى ان عصر تطبيقات الذكاء الاصطناعي قد بدأ بالفعل ويجب على الباحثين والتدريسين الاستفادة من هذه التقنية، ومن الضروري توخي الحذر والنظر في الآثار المحتملة لتلك التقنيات، والتأكد من استخدامها بطريقة مسؤولة وأخلاقية.

نظمت كلية التربية بجامعة الكوفة ورشة عمل بعنوان (المعرفات العالمية واشهار البحوث ) حضرها عدد من التدريسيين والطلبة ، تضمنت محاضرة للتدريسي ايمن العوادي تحدث فيها عن ضرورة مشاركة الكادر التدريسي في منصات البحث العلمي بهدف اشهار بحوثهم العلمية وتحديث معلوماتهم الشخصية والبحثية في المنصات البحثية والعلمية، مشيراً الى آلية التواصل العلمي بين الباحثين من مختلف دول العالم.

أقيمت في مركز البحث والتأهيل المعلوماتي ورشة عمل بعنوان (نحو مجلات علمية رصينة في جامعة الكوفة) تم عرض الامكانات التي يوفرها نظام المجلات الحالي من ناحية ارشفة البحوث في مواقع الارشفة العالمية مثل (Google Scholar و DOAJ) وقد تم طرح ومناقشة الية تقديم المجلات للأرشفة ضمن ارشفة Scopus العالمية, اذ يعد واحد من اكبر واشهر مواقع الارشفة العالمية الرصينة للمجلات والكتب, وتعد هذه الخطوة الثالثة من استراتيجية مركز البحث والتأهيل المعلوماتي في تقديم الخدمات الالكترونية للمجلات بعد تقديم خدمة الاستضافة الحالية للمجلات وجعل جميع البحوث المنشورة فيها بصورة الكترونية قابلة للأرشفة وبعدها تم بالفعل ارشفة جميع المجلات تحت ارشفة Google Scholar وبعض مواقع الارشفة المشهورة, ثم خطوتنا الحالية بحث القائمين على المجلات لترصين مجلاتهم اكثر وتقديمها للأرشفة ضمن Scopus. وقد ابدى محرري المجلات رغبة كبيرة في محاولة التقديم, كما وقد تم التأكيد ان هذه الخطوة هي ليست الاخيرة.

يقيم مركز البحث و التاهيل المعلوماتي سيمينار بعنوان " Digital forensics " وذلك يوم 17/11/2015 على قاعة المؤتمرات الفديوية الساعة الثانية عشر ظهرا , يلقي السيمنار المحاضر م.م ايمن حسن رشيد