Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userA Study of QoS in Long Term Evolution Networks "LTE"
دراسة جودة الخدمة في شبكات التطوير بعيد المدى "LTE"
2975
4 229
0
(
0
)
Created by
Shamra Editor
Ask ChatGPT about the research
تعتبر تقنية التطوير بعيد المدى "LTE" من أحدث تقنيات الاتصالات التي تندرج ضمن تقنيات الجيل الرابع من الاتصالات الخلوية، و التي تدعم سرعات عالية و عرض حزمة كبير، بالإضافة لتقديمها إمكانيات للتعامل مع جودة الخدمة المرتبطة بأنواع محددة من البيانات، نتيجةً لذلك فإنها تحظى باهتمام واسع و كبير من الباحثين و المستخدمين. إن التحدي الأكبر الذي يواجه شبكات التطوير بعيد المدى "LTE" هو القدرة على ضمان جودة الخدمة لكل مستخدمي الشبكة طالما هذه الشبكات تخدّم كل من مستخدمي الصوت و البيانات بنفس الوقت، لذلك جاءت دراستنا لتبين أثر مجموعة من خوارزميات الجدولة على انتقال بيانات "TCP" و بيانات صوتية و فيديوية.
Long Term Evolution “LTE” is considered to be one of the most important and latest communication technologies falling under the fourth generation of cellular communications technology 4G. LTE supports high-speed and large bandwidth which makes it a great candidate to providing the potential to improve the Quality of Service "QoS" associated with specific types of data transfer. As a consequence, researchers have paid their attentions to this type of networks. In fact, it was a great challenge for researchers to achieve a good level of QoS for all users as the LTE provides Audio and Data transmission to users at the same time.
Artificial intelligence review:
Research summary
تتناول هذه الدراسة تقنية التطوير بعيد المدى (LTE) التي تعد من أحدث تقنيات الاتصالات ضمن الجيل الرابع. تهدف الدراسة إلى تحليل تأثير خوارزميات الجدولة المختلفة على جودة الخدمة (QoS) في شبكات LTE، خاصة فيما يتعلق بنقل بيانات TCP، الصوت والفيديو. تم استخدام محاكي الشبكات NS3 لإجراء التجارب وتحليل معايير جودة الخدمة مثل التأخير الزمني (Delay)، الإنتاجية (Throughput)، والإزاحة الزمنية بين الرزم (Jitter). أظهرت النتائج أن خوارزمية Round Robin تعطي أفضل أداء في بعض الحالات، بينما خوارزمية Channel and QoS Aware (CQA) تعطي أقل تأخير زمني. الدراسة تقدم توصيات لاختيار الخوارزمية الأنسب لكل نوع من البيانات.
Critical review
تعتبر هذه الدراسة خطوة مهمة نحو فهم تأثير خوارزميات الجدولة على جودة الخدمة في شبكات LTE. ومع ذلك، هناك بعض النقاط التي يمكن تحسينها. أولاً، كان من المفيد تضمين تحليل أكثر تفصيلاً حول كيفية تأثير العوامل البيئية مثل الضوضاء والتداخل على أداء الخوارزميات. ثانياً، الدراسة تركز بشكل كبير على محاكي NS3، وكان من الممكن تعزيز النتائج باستخدام محاكيات أخرى مثل Opnet أو Omnet لتقديم رؤية أكثر شمولية. أخيراً، كان من الممكن تقديم توصيات أكثر وضوحاً حول كيفية تطبيق هذه الخوارزميات في بيئات حقيقية.
Questions related to the research
-
ما هي الخوارزميات التي تم دراستها في هذه الورقة؟
تم دراسة أربع خوارزميات جدولة وهي: Round Robin، Priority Set، Channel and QoS Aware، وProportional Fair.
-
ما هو المحاكي الذي تم استخدامه في الدراسة؟
تم استخدام محاكي الشبكات NS3 لإجراء التجارب وتحليل النتائج.
-
ما هي معايير جودة الخدمة التي تم تحليلها في الدراسة؟
تم تحليل معايير التأخير الزمني (Delay)، الإنتاجية (Throughput)، والإزاحة الزمنية بين الرزم (Jitter).
-
ما هي الخوارزمية التي أعطت أفضل أداء في نقل بيانات الصوت؟
خوارزمية Round Robin أعطت أفضل أداء في نقل بيانات الصوت.
References used
Shukla S , Khare V , Garg S, Sharma P, Comparative Study of 1G, 2G, 3G and 4G, Journal of Engineering, Computers & Applied Sciences (JEC&AS), V.2, No.4, P:55-63, 2013
Bhalla M, Bhalla A. , Generations of Mobile Wireless Technology, International Journal of Computer Applications,V.5, No.4,P:26-32, 2010
Yusof A, Kuokkwee W, Ee Mae A, Mohd A. , Performance Study of Channel-QoS Aware Scheduler in LTE Downlink Using NS3, The Seventh International Conference on Emerging Networks and Systems Intelligence,p:44-49, 2015
rate research
Read More
Several new technologies had been presented in LTE system
standards in order to achieve higher performance and more
reliability than Previous cellular communications systems. The
added new standards describe advanced technologies that integrated
into the system environment so that we can meet subscribers
Growing requirements. in this study we'll discuss in details the
different patterns of modulation schemes, which are adopted in (3
GPP) standards for (LTE) system downlink.
Research paper on the TCP protocol and its handling of bottlenecks, with a simple comparison between several copies of the protocol.
Route discovery in infrastructure based network is an important problem. Normally, route selection or route discovery is done based on the shortest path principle. In infrastructure based networks، a number of issues for route discovery need to be ad
dressed as the packet flow are prone to errors making the routing operation failure. Reliability, for example، is an important issue for route discovery. Ensuring Quality of Service (QoS) is important and is to be taken care while forwarding a packet flow. In this paper، a model for route discovery in infrastructure based networks using GA is being proposed. Out of many paths available from the gateway of the network to the final destination, the one is selected which satisfies the desired QoS. Two important QoS parameters، path loss and processing time at the router (Base Station), have been considered. The experimental results for both the QoS parameters reveal the efficacy of the model.
Language models are generally trained on short, truncated input sequences, which limits their ability to use discourse-level information present in long-range context to improve their predictions. Recent efforts to improve the efficiency of self-atte
ntion have led to a proliferation of long-range Transformer language models, which can process much longer sequences than models of the past. However, the ways in which such models take advantage of the long-range context remain unclear. In this paper, we perform a fine-grained analysis of two long-range Transformer language models (including the Routing Transformer, which achieves state-of-the-art perplexity on the PG-19 long-sequence LM benchmark dataset) that accept input sequences of up to 8K tokens. Our results reveal that providing long-range context (i.e., beyond the previous 2K tokens) to these models only improves their predictions on a small set of tokens (e.g., those that can be copied from the distant context) and does not help at all for sentence-level prediction tasks. Finally, we discover that PG-19 contains a variety of different document types and domains, and that long-range context helps most for literary novels (as opposed to textbooks or magazines).
Many researches showed the ability of advance reservation to improve the predictability of the
system; that allows it to deliver the applications required time constrains. Applications with
many tasks require the system to ensure a number of reserv
ations on many different distributed
resources, which usually carried out through multi-level negotiation adding by that additional
overhead on the application total response time. The extra overhead depends on many
parameters including system workload and contention. Workflows add more complexity due to
their tasks’ dependencies; thus, any rejection of or delay for a task reservation would increase
application complete time.
This paper suggests the use of elastic advanced reservation plans that depend on time gaps
presented in the sub-optimal schedules, in order to improve the reservation acceptance rate. It
presents an elastic co-reservation agent which provides the needed reservations using First Fit
allocation strategy.
The results show the ability of the proposed agent to always improve the acceptance rate with an
average of (22.25%). The more important came out result is the agent ability to increase the
reservation acceptance rate with the increasing of system competence, reaching (48.4%) for
simultaneous 90 users at the system.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
