No abstract

Network Traffic Monitoring and Analysis (NTMA) is the main element to network management, especially to correctly operate large-scale networks such as the Internet on which modern academic organizations heavily depend. Their traffic use increases significantly because students, staff members, and research labs use them to search information. It is necessary to analyze, measure, and classify this Internet traffic according to the need of different stakeholders such as Internet Service Providers and network administrators. Moreover, bandwidth congestions frequently occur, causing user dissatisfaction. This study tries to find different characterizations such as data over hosts, countries, cities, companies, top-level domains, and servers. In addition, this is a new study to find out different patterns and levels of analysis from the device to its international requests. Our findings show that the highest traffic use is on Mondays and Wednesdays. Web server and DNS server drop in response to fault tolerance. Social networks consume most of the bandwidth, such as 42% Facebook followed by 22% WhatsApp in peak hours. The second most accessed sites are search engines. Google is the most used one. About 59% of the host cities are outside Iraq, in particular USA and the UK. In Amara and Baghdad cities, the requested sites are 51% and 49% overseas. About 40% of the traffic is provided by EarthLink Ltd. Communication Internet services (Iraq), 14% EdgeCast. 12% level3, 9% Facebook, 7% Google, Akamai-as and Microsoft-corp-msn-as-block. This study gives guidelines for network administrators to improve their performance and bandwidth at the educational networks.

Typical steady state studies always treat the peak power demands as the worst case conditions. Periods of light load are also critical in the assessment of the possible state of a power system. While heavy load conditions are generally associated with overload, low voltage and generation deficiency, light load conditions may give rise to over-voltage and undesirable reactive power requirements at generation side. This paper focus on study the effect of DG Optimizing on overload Transmission line Stability. The system dispatch constraints should be taken into account to compensate or varying DG generation output and to enhance the operational performance of power systems. This dispatching operation depends on the change of DG generation and the dispatching strategy. The impact of DG generation uncertainty is limited with the generation dispatching operation and should not be neglected in system analysis.