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Register a new userA comparative study of compression algorithms and their impact on data communication in networks
دراسة مقارنة لخوارزميات الضغط و أثرها على تراسل المعطيات في الشبكات
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Added by
Tishreen University ورقة بحثية
Publication date
2018
fields
Electrical Power Engineering
and research's language is
العربية
Authors
دريد عجيب( باحث )
Created by
Shamra Editor
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نظرا للتزايد الكبير لاستخدام تراسل البيانات و خدمات تبادل المعلومات بأنواع مختلفة ضمن بيئات متباينة عتادياً و برمجياً كان لابد من وجود لغة توصيف مثالية قابلة للتوسع و التطوير تخدم هذه الاحتياجات المتزايدة بأفضل شكل و بأقصر وقت ممكن و كانت اللغة الاكثر انتشاراً و الأكثر استخداماً لغة XML. كما أن اعتماد بنية الرسوميات احياناً خلق مشكلة أثرت على أداء شبكات نقل المعلومات نظرا للحجم الكبير للبيانات المتبادلة و كذلك الحاجة لسعة تخزينية كبيرة في طرفي الارسال و الاستقبال لذا كان لابد من إيجاد طرق فعالة لإنقاص حجم تلك البيانات التي يتم تبادلها من خلال الشبكة. تم إجراء العديد من الأبحاث العلمية و التجارب العملية حول إيجاد طرق فعالة لإنقاص الحجم الفعلي للبيانات و باعتماد بارامترات مختلفة تؤثر على عملية ضغط الملفات بحيث تحقق نتائج أفضل بالتقليل من حجوم الملفات المتبادلة مع الانتباه الى أزمنة ضغط و فك الضغط للملفات. لذا تم التركيز في هذا البحث على دراسة و مقارنة لبعض خوارزميات الضغط للملفات و بيان أثرها على تراسل البيانات في الشبكات.
Due to the large increase in the use of data communication and information exchange services of different types in different environments, the standard and the programming had to be a language of characterization is ideal for scalability and development that serve the growing needs in the best form and in the shortest possible time and was the most widely used language and the most widely used XML language. he adoption of graphics architecture sometimes created a problem affecting the performance of information transmission networks due to the large volume of data exchanged as well as the need for large storage capacity at both ends of the transmission and reception. Effective ways of reducing the amount of data exchanged through the network had to be found. There have been many scientific researches and practical experiments on finding effective ways to reduce the actual size of the data and by adopting different parameters that affect the process of compressing the files so as to achieve better results by reducing the volumes of files exchanged with attention to times of compression and decompression of files. In this research, we focused on the study and comparison of some compression algorithms for files and their effect on data communication in networks.
Artificial intelligence review:
Research summary
تتناول هذه الدراسة المقارنة بين خوارزميات الضغط المختلفة وتأثيرها على تراسل البيانات في الشبكات. مع تزايد استخدام لغة XML في تبادل البيانات عبر الشبكات، ظهرت الحاجة إلى تقنيات ضغط فعالة لتقليل حجم البيانات المرسلة والمستقبلة. يركز البحث على مقارنة خوارزميات مثل GZip وXMill وXGrind من حيث معدل الضغط، زمن الضغط، وزمن فك الضغط. أظهرت النتائج أن خوارزمية XMill تحقق أفضل معدل ضغط وأقل زمن للضغط مقارنة بخوارزمية XGrind، بينما خوارزمية GZip توفر معدل ضغط جيد ولكنها قد تكون أقل كفاءة في بعض الحالات. توصي الدراسة باستخدام خوارزمية XMill خاصة للملفات الكبيرة، مع إمكانية استخدام أكثر من خوارزمية لضمان أفضل أداء.
Critical review
دراسة نقدية: تعتبر هذه الدراسة مهمة في مجال تحسين أداء الشبكات من خلال تقنيات الضغط، ولكن كان من الممكن أن تكون أكثر شمولية إذا تناولت المزيد من الخوارزميات الحديثة. كما أن الدراسة تركز بشكل كبير على لغة XML، وكان من الممكن أن تشمل لغات أخرى أو أنواع بيانات مختلفة. بالإضافة إلى ذلك، كان يمكن تحسين الدراسة بإجراء تجارب على نطاق أوسع من البيانات لتقديم نتائج أكثر دقة وشمولية.
Questions related to the research
-
ما هي الخوارزمية التي حققت أفضل معدل ضغط في الدراسة؟
خوارزمية XMill حققت أفضل معدل ضغط في الدراسة.
-
ما هي أهمية استخدام تقنيات الضغط في شبكات البيانات؟
تقنيات الضغط تقلل من حجم البيانات المرسلة والمستقبلة، مما يحسن من أداء الشبكة ويقلل من زمن الإرسال والتخزين.
-
ما هي العيوب المحتملة لخوارزمية GZip وفقًا للدراسة؟
خوارزمية GZip قد تكون أقل كفاءة في بعض الحالات، خاصة عند التعامل مع ملفات كبيرة الحجم.
-
ما هي التوصيات التي خلصت إليها الدراسة بشأن استخدام خوارزميات الضغط؟
توصي الدراسة باستخدام خوارزمية XMill للملفات الكبيرة، مع إمكانية استخدام أكثر من خوارزمية لضمان أفضل أداء.
References used
SOHAIL ANSARI ; PRAJEET SHARMA , XML Optimization and Compression , International Journal of Innovations & Advancement in Computer Science , March 2015
SHERIF SAKR , Investigate state-of-the-art XML compression techniques , IBM Corporation , 19 July 2011
WILFRED NG ; WAI-YEUNG LAM ; JAMES CHENG , Comparative Analysis of XML Compression Technologies , March 2006
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