scholarly journals Proactive Two-Tier Bandwidth Brokerage for On-Demand Policy-Based Resource Allocation in Stateless IP Networks

2005 ◽  
pp. 350-361 ◽  
Author(s):  
Kamel Haddadou ◽  
Yacine Ghamri-Doudane ◽  
Samir Ghamri-Doudane ◽  
Nazim Agoulmine
Keyword(s):  
Resource Allocation ◽  
Ip Networks ◽  
On Demand

Practical and analytical approaches for designing scalable on-demand policy-based resource allocation in stateless IP networks

2011 ◽  
Vol 22 (2) ◽  
pp. 131-149 ◽  
Author(s):  
Kamel Haddadou ◽  
Samir Ghamri-Doudane ◽  
Yacine Ghamri-Doudane ◽  
Nazim Agoulmine
Keyword(s):  
Resource Allocation ◽  
Ip Networks ◽  
On Demand ◽  
Analytical Approaches

Designing scalable on-demand policy-based resource allocation in IP networks

2006 ◽  
Vol 44 (3) ◽  
pp. 142-149 ◽  
Author(s):  
K. Haddadou ◽  
S. Ghamri-Doudane ◽  
Y. Ghamri-Doudane ◽  
N. Agoulmine
Keyword(s):  
Resource Allocation ◽  
Ip Networks ◽  
On Demand

On Demand Priority Packet Forwarding for TCP Performance Enhancement in Cognitive Mobile IP Networks

2015 ◽  
Vol 86 (4) ◽  
pp. 1947-1970
Author(s):  
Satish Anamalamudi ◽  
Minglu Jin ◽  
Jae Moung Kim ◽  
Chang Liu
Keyword(s):  
Performance Enhancement ◽  
Mobile Ip ◽  
Ip Networks ◽  
Packet Forwarding ◽  
Tcp Performance ◽  
On Demand

On Demand Resource Allocation for LTE Uplink Transmission Based on Logical Channel Groups

2017 ◽  
Vol 22 (5) ◽  
pp. 868-879 ◽  
Author(s):  
Fang-Chang Kuo ◽  
Kuo-Chang Ting ◽  
Hwang-Cheng Wang ◽  
Chih-Cheng Tseng
Keyword(s):  
Resource Allocation ◽  
On Demand ◽  
Logical Channel ◽  
Lte Uplink

Resource Allocation Policies in Cloud Computing Environment

2017 ◽  
pp. 115-132 ◽  
Author(s):  
Suvendu Chandan Nayak ◽  
Sasmita Parida ◽  
Chitaranjan Tripathy ◽  
Prasant Kumar Pattnaik
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Resource Utilization ◽  
Service Level Agreement ◽  
Service Level ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
On Demand ◽  
Different Types ◽  
Cloud Datacenter

The basic concept of cloud computing is based on “Pay per Use”. The user can use the remote resources on demand for computing on payment basis. The on-demand resources of the user are provided according to a Service Level Agreement (SLA). In real time, the tasks are associated with a time constraint for which they are called deadline based tasks. The huge number of deadline based task coming to a cloud datacenter should be scheduled. The scheduling of this task with an efficient algorithm provides better resource utilization without violating SLA. In this chapter, we discussed the backfilling algorithm and its different types. Moreover, the backfilling algorithm was proposed for scheduling tasks in parallel. Whenever the application environment is changed the performance of the backfilling algorithm is changed. The chapter aims implementation of different types of backfilling algorithms. Finally, the reader can be able to get some idea about the different backfilling scheduling algorithms that are used for scheduling deadline based task in cloud computing environment at the end.

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