Resource Reservation

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SDN Based Resource Reservation Protocol for IoT applications in Constrained Networks

SDN Based Resource Reservation Protocol for IoT applications in Constrained Networks

deployed[3]. Sensor nodes are constrained in its resources like memory, power, size, processing, and bandwidth. WSN has a varied and large number of applications in almost all fields of human life interactions. These applications have heterogeneous data to be sensed and transmitted with different QoS requirements. As some human life-saving applications require a infalliable and timely end to end delivery, the resource-constrained nature of WSN poses challenges to guarantee the required reliable, definitive and timely delivery of such application [4]. For reliable and timely delivery; resources need to be managed optimally along the path from the node until the data reaches the base station. The energy of each sensor node is constrained since it is battery operated and hence it needs to be optimally utilized so that end to end communication of critical data could be achieved reliably and within time. This can be accomplished by managing the resources efficiently and fairly by reserving the required resources along the path to the destination. Also, the efficiency of resource management and end-to-end QoS can be augmented by designing appropriate resource reservation mechanisms. Resource reservation in WSN is a demanding and challenging task as there is no prior information about event occurrences in future, reservations must be preserved in a confined environment and data may need to be transmitted periodically. Integrated Services is one such approach that aids to satisfy the needs of QoS-demanding applications. Applications convey their QoS requirements to the network efficiently and robustly by means of RSVP[5]. RSVP is the main component of the Integrated Services of Internet which provides best-effort and real-time service[6][7]. RSVP for traditional networks is a network control protocol specified in RFC 2205. RSVP does not provide any network service; it communicates the end-to- end system requirements to the network[8] permitting the receiver to appeal an end-to-end QoS for its data flows and reserving needed resources at routers along the path in real- time applications. All nodes in the data path must be RSVP compliance for an assured QoS. Resource reservation challenges of WSN are inherited from traditional wireless networks, such as time-varying channels and unreliable links along with characteristics of WSNs, such as severe resource constraints and harsh environmental conditions[6]. These Resource Reservation challenges for WSNs are discussed below:Resource constraints: WSNs are limited in resources such as bandwidth, memory, energy and processing capability.
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Resource Reservation in Real-Time Operating Systems - a joint industrial and academic position

Resource Reservation in Real-Time Operating Systems - a joint industrial and academic position

Real -time control systems (such as robotics) have always been the domain of hard real-time scheduling. Recent study [24] has shown that the use of resource reservation techniques can bring advantages in terms of control performance. Designing the system for the worst-case guarantees absence of deadline misses, but can impose a low control loop rate. On the other hand, designing the system for the average case allows increasing the control loop rate, and thus improving the control performance, in the average case, but can lead to deadline misses of critical activities. Resource reservation techniques permit to calibrate the resource usage for the different activities. For example, in a complex control system with multi-rate sensor acquisition that uses a video camera for pattern recognition, the most critical low-level control loop can be considered as a hard activity, which should be assigned an amount of resource equal to its worst-case requirement. The less critical activities, like image acquisition and recognition, can be assigned a fraction of the resource equal to their average case conditions, thus increasing their rate [23][24].
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Resource Reservation in Grid Networks based on Irregular Cellular Learning Automata

Resource Reservation in Grid Networks based on Irregular Cellular Learning Automata

SP2 supercomputer systems on Extensible Argonne Scheduling system (EASY) local scheduling system. The backfilling technique is considered as one of the most popular methods for improving the utilization rate of reservation-based resources. Generally, the backfilling technique is classified into two groups: Aggressive Backfilling Reservation Policy (ABRP) and Conservative Backfilling Reservation Policy (CBRP) [11]. However, the cellular automata-based methods have been considered for scheduling requests in the grid network in the recent decade [12, 13]. For example, Yeh and Wei [14] have presented an economic resource allocation model to obtain the service reliability of grid computing networks through Cellular Automata Monte Carlo Simulation (CA- MCS). A new cellular automata-based algorithm was proposed for scheduling independent tasks with aim of optimizing the time in economic computational grids [13]. An evolutionary cellular automata-based scheduling method based on genetic algorithm was proposed in another study for scheduling parallel processing in multi-processor systems [15]. Another study presented and evaluated the learning automata- based algorithms called LATO and ALATO for scheduling the tasks with the aim of minimizing the execution time of applications [16]. An Overlapped Advance Reservation Policy (OARS) was introduced to reduce the negative effects of advance allocation of resources (advance reservation), in a way that allowed a new reservation request that overlapped with current reservations be accepted in the system under certain circumstances. This policy shows more compliance when grid systems have high reservations rates [17]. In addition, several algorithms have been proposed for resource reservation in the grid networks; for example refer to [18-20].
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Heuristic Based Resource Reservation Strategies for Public Cloud

Heuristic Based Resource Reservation Strategies for Public Cloud

A lot more methodologies exists, to give solutions to resource reservation claims and most of them have integer programming problem (IPP), which is NP in nature. In this work we derive heuristic methodological algorithm to find some near optimal solution to the problem initially by putting restrictions, later these restrictions are removed. We used Best-fit heuristic to achieve sub-optimal solutions, in this presenting work. Best-Fit heuristic algorithm attempts to approximate Bin-Packing strategy; which we have chosen in comparison with Exact Virtual Machine allocation proposal. Allocation and migration algorithms are used to minimize overall data-center power consumption.
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A Total Need based Resource Reservation Technique for Effective Resource Management

A Total Need based Resource Reservation Technique for Effective Resource Management

The motivational example in section 2, demonstrate that Banker’s Algorithm will always estimate the safety sequence by considering the requirement for all the processes in the system. However, this cross checking incurs as overhead . This paper proposes the resource reservation techniques in which the system reserves a pool of resources. These reserved resources can be allocated to only those processes those total resources need can be satisfied by them, i.e., a process who will not require any resources further and will finish its execution. The remaining resources are freely available and can be allocated to any requesting process. Thus, when a process demands for resources which are not freely available then the system must release the reserve pool resources provided the total need of the process can be satisfied. Hence, it will complete and relieve all the resources it is holding.
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Comparative Analysis of Various Advance Resource Reservation Algorithms In Grid Computing Environments

Comparative Analysis of Various Advance Resource Reservation Algorithms In Grid Computing Environments

In the ORR (Optimal Resource Reservation) approach the best fetch strategy is considered. During reservation, if the slots requested are empty then they are reserved. The conflict occurs only when the slots are not available. Normally, the reservation denial is done in FCFS approach. In TARR, the free slots are considered and the reservation slots are provided rather than as a single slot. For this purpose, in addition to the proposed start time and finish time, the defer time (DT) is also considered. The defer time is time until which the job can be completed or considered for reservation. In TARR approach, whenever a free slot is available it is allotted as such. TARR necessitates more context switching i.e., whenever a small chunk of time slice is available, then that is reserved which requires more process suspension and resumption. The entity resource can be reserved for a period of time. After the elapse of time the current process in execution need to undergo process switching. The current status of the PCB (Process Control Block) is stored. And the detail on process to be resumed is retrieved. The new process possesses the resource. The state transition or process switching causes additional overhead. Hence in this ORR the slicequeue and select slicequeue are maintained [6].
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Resource Reservation protocol Tunnelling Extension in MPLS for sustainable Mobile Wireless Networks

Resource Reservation protocol Tunnelling Extension in MPLS for sustainable Mobile Wireless Networks

Abstract— Traffic Engineering (TE) is most effective in networks where some links are heavily utilized and have little or no bandwidth available while others carry little or no traffic. It is of great importance to the recent development of mobile and wireless technologies. Without the process of TE, there is possibilities of having under-utilization and over-utilization problems along the links. It is necessary to consider the implementation that would avoid the goal of network and unguaranteed bandwidth delivery. Therefore, the operators and service providers require seamless combination of network protocols with an improved quality of service (QoS). This paper will be focusing on Resource Reservation Protocol Tunnelling Extension Multiprotocol Layer Switching (RSVP-TE MPLS) for sustainable mobile wireless networks. This will make provision of bandwidth allocation possible by implementing the configurations of the dynamic and static LSPs (Label Switching Paths). The network model designed will be used for this purpose by using simulation approach. The verification of the MPLS model will be presented. It will eventually maximize bandwidth utilization, minimize operation cost and improve QoS.
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Radio resource reservation for heterogeneous traffic in cellular networks with spectrum leasing

Radio resource reservation for heterogeneous traffic in cellular networks with spectrum leasing

Radio channel reservation is used to alleviate call dropping which may occur in two situations: (i) hand-off between cells in cellular networks, and (ii) channel withdrawal in wireless networks with spectrum leasing. In this article, we study a radio resource reservation scheme for heterogeneous traffic in a cellular network with spectrum leasing, in which one reservation pool is used to alleviate the two types of call droppings. Since different types of traffic have different tolerances to the exhaustion of channels, it is critical for different types of traffic to select the optimal size of the reservation pool such that the channel requirements of different types of traffic are satisfied while throughput is maximized. A three-dimensional Markov chain is presented to find the optimal size of reservation pool. Numerical and simulation results show that (i) the selected parameters of reservation satisfy the quality-of-service requirements of different types of traffic while produce high throughput, and (ii) channel withdrawal yields higher impact on real-time traffic than non-real-time traffic in terms of throughput.
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AutoAdmin: Automatic and Dynamic Resource Reservation Admission Control in Hadoop YARN Clusters

AutoAdmin: Automatic and Dynamic Resource Reservation Admission Control in Hadoop YARN Clusters

The comparison between the optimal reservation results obtained through experiments and the prediction ones is shown in Table 3.1. As we can observe, the predicted values (i.e., the number of reserved vcores, shown in the parenthesis) are close to the optimal reservation in most cases. However, the amount of resources that need to be reserved is underestimated when the resource requirement of AM is much larger than the resource requirement of normal tasks. Under such a case, the benefit of accelerating each job’s execution, i.e., reserving more resources for processing tasks, clearly surpasses the benefit of allowing higher concurrency between jobs, i.e., allowing AMs to occupy more resources. That is because jobs release a large amount of resources that are occupied by their AMs more quickly when they can finish their execution faster. To improve the accuracy of prediction under the extreme cases, we simply set a lower bound for resource reservation as 40% of the total cluster resources according to our observations. New prediction values are shown in Table 3.2.
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Implementation of Traffic Engineering in MPLS Networks by Creating TE Tunnels Using Resource Reservation Protocol and Load balancing the Traffic

Implementation of Traffic Engineering in MPLS Networks by Creating TE Tunnels Using Resource Reservation Protocol and Load balancing the Traffic

ABSTRACT: Today Internet Plays an important role in our day-to-day life. Basically, WAN connections are expensive in ISP’s budget and it is most important to deliver the services with QoS to its customers. Traffic Engineering is one of the solution when routers are overloaded. Generally, all routers in the network uses the shortest path. By this all routers are overloaded and traffic occurs.This results in packet delay or dropping in the network. The main objective of this project is to forward the packets using tunnels, when the traffic occurs. The headend router uses Resource Reservation protocol to reserve the bandwidth to forward the packets. And finally the enhanced Quality of Service (QoS) is achieved by this project.
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Resource reservation for mobile hotspots in vehicular environments with cellular/WLAN interworking

Resource reservation for mobile hotspots in vehicular environments with cellular/WLAN interworking

In this article, we investigate the resource reservation issue for moving networks in a vehicular environment. A two-hop relay structure integrates heterogeneous technologies of the cellular network and wireless local area network. Focusing on the ever-increasing video applications, we have introduced feasible analytical approaches to effectively evaluate video performance in terms of data loss rate and packet delay. To satisfy video QoS constraints, we can derive the bandwidth to be reserved for handover. Our performance evaluation has taken into account the two-hop relay structure and the essential characteristics of video traffic. At the flow level, we use a sigmoid function to model video flows as a Markov-modulated process and calculate data loss rate with fluid-flow analysis. At a finer packet level, due to inter-coded frames, video traffic arrives in bursts and results in transmission packets as a batch for each video burst. Our queueing analysis for packet delay has con- sidered this feature and provided fairly accurate esti- mate. On the other hand, video flows from end users within a vehicular network can be multiplexed at a local gateway. As the aggregate traffic exhibits self-similarity, we use a FBM process to characterize the aggregate traf- fic flow beyond the wireless gateway. The data loss rate and packet delay for the second hop are approximated accordingly. As demonstrated in the numerical exam- ples, the performance evaluation can be applied to
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Enhancing Resource Reservation by Applying Defer Time in FCFS Scheme for Grid Computing Environments

Enhancing Resource Reservation by Applying Defer Time in FCFS Scheme for Grid Computing Environments

particular node. Sharing enables the efficient utilization of resources. The grid environment is highly unpredictable as nodes and the associated resources may enter or leave the environment at any time. This feature makes the necessity for more improved methods towards resource management. The resource management includes the resource discovery, resource allocation and resource reservation. There were various tools available for grid computing as Globus ToolKit, Nimrod – G, Condor – G, Legion etc. The MDS handles the monitoring and discovery of services in the grid environment.
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Burstiness of virtual machine resource reservation in Cling firefly optimizationoud us

Burstiness of virtual machine resource reservation in Cling firefly optimizationoud us

In computing clouds, burstiness of a virtual machine (VM) workload widely exists in real applications, where spikes usually occur aperiodically with low frequency and short duration. This could be effectively handled through dynamically scaling up/down in a virtualization-based computing cloud; however, to minimize energy consumption, VMs are often highly consolidated with the minimum number of physical machines (PMs) used. In this case, to meet the dynamic runtime resource demands of VMs in a PM, some VMs haveto be migrated to some other PMs, which may cause potential performance degradation. In this paper, we investigate the burstinessaware server consolidation problem from the perspective of resource reservation.
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Stochastic Analysis of a resource reservation system

Stochastic Analysis of a resource reservation system

Once interrupt handlers have been transformed into schedulable entities, the problem remains open of identifying the best scheduling algorithm that can be used to serve the newly introduced threads. For example, Manica et al. [54, 55] have provided a clear evidence that using resource reservations [5] to schedule the interrupt han- dlers (IRQ threads, in Preempt-RT) allows the designer to find ap- propriate trade-offs between the response time of real-time tasks and the device throughput (this is important when the device is used by real-time tasks). However, to the best of our knowledge, most ex- periments and tests with advanced scheduling solutions have been performed only using prototypical schedulers or experimental Oper- ating Systems [56, 43]. Only recently has a Linux scheduler based on resource-reservation has been proposed to the kernel community [57]. Such a scheduler exports an API that can be easily used to schedule kernel threads implementing the device drivers. Additionally, most of the previous work has focused on network devices [47, 48, 44, 51, 55] paying little or no attention to other types of devices (e.g., disks). Fi- nally, another limitation of previous results is that they are mostly collected on artificial task sets.
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Enhancement Of Wireless Sensor Network Qos Using Linear Resource Reservation Congestion Control Protocol (LRRCCP)

Enhancement Of Wireless Sensor Network Qos Using Linear Resource Reservation Congestion Control Protocol (LRRCCP)

This paper has presented the behavioral descriptions of a Linear Resource Reservation Congestion Control Protocol for a linear pipeline infrastructure. The LRRCC mitigates congestion and allocates appropriate resources to the sensor nodes and sink node in the linear sensor network model. LRRCC comprises of these phases: congestion detection phase based on priority assignment, data rate adjustment phase and buffer size occupancy phases. It maintains the global flow information from the sources (BSN) to the sinks. The proposed scheme is expected to mitigate congestion at a very high efficiency compared to other schemes. Each node in the network individually allocates or reduces the data rate of upstream or downstream neighbors to avoid the congestion as shown in Fig 3. The parameters for variations and analysis will be presented in future studies.
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Dynamic Resource Reservation and Connectivity Tracking to Support Real Time Communication among Mobile Units

Dynamic Resource Reservation and Connectivity Tracking to Support Real Time Communication among Mobile Units

Wireless communication technology is spreading quickly in almost all the information technology areas as a consequence of a gradual enhancement in quality and security of the communication, together with a decrease in the related costs. This facili- tates the development of relatively low-cost teams of autonomous (robotic) mobile units that cooperate to achieve a common goal. Providing real-time communication among the team units is highly desirable for guaranteeing a predictable behavior in those applications in which the robots have to operate autonomously in unstructured environments. This paper proposes a MAC protocol for wireless communication that supports dynamic resource reservation and topology management for relatively small networks of cooperative units (10–20 units). The protocol uses a slotted time-triggered medium access transmission control that is collision-free, even in the presence of hidden nodes. The transmissions are scheduled according to the earliest deadline first scheduling policy. An adequate admission control guarantees the timing constraints of the team communication requirements, including when new nodes dynamically join or leave the team. The paper describes the protocol focusing on the consensus proce- dure that supports coherent changes in the global system. We also introduce a distributed connectivity tracking mechanism that is used to detect network partition and absent or crashed nodes. Finally, a set of simulation results are shown that illustrate the effectiveness of the proposed approaches.
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Burst Stream Resource Reservation Algorithm of Satellite E OBS Network Based on Preemption Window

Burst Stream Resource Reservation Algorithm of Satellite E OBS Network Based on Preemption Window

Resource reservation procedure refers to preemptive window scheme based on window [4,12] .All the BDP is classed into High Priority (HP) and Low Priority (LP), and every class BDP is allocated some data channels. When HP BDP’s corresponding data channel is busy it will preempt LD BDP’s reserved channels. The preemptive condition is following: the arriving time of HP BCP must be in the range of preemptive window T, and LP BDP hasn’t transmitted, or the preempt will be forbidden. Fig.1 shows the procedure of onboard switching based on preemptive window.
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Resource Reservation in Shared and Switched Demand Priority Local Area Networks

Resource Reservation in Shared and Switched Demand Priority Local Area Networks

effects since different flows may interact across different segments. Once the distortions have been characterized, appropriate resources can be reserved to maintain the quality of service. This often results in buffer space requirements increasing monotonically with the number of hops in the data path [PaGa94], [BeZh96a], [GVC96]. The important advantage of work conserving schemes how­ ever is that resource shares are only enforced under overload. Whenever flows do not use the band­ width reserved for them, then this can be used by other flows using the same or any other service. In contrast, non-work conserving service disciplines reshape arriving data flows and thus recon­ struct a flow’s traffic pattern before the forwarding to the next switch. This simplifies the network analysis and ensures that buffer space requirements remain constant along the data path [Zhan95]. Beside providing a delay bound, some schemes can additionally control the delay jitter [KaKa90], [ZhFe93]. Holding data packets in switches however results in higher average packet delays [Zhan95] and requires a traffic shaping mechanism such as the (Ô, r) regulator [ZhFe93] or a fram­ ing strategy [Gole90]. In contrast to work conserving schemes, non-work conserving service disci­ plines enforce resource shares regardless of the current work load. Data flows are thus rate regulated even when sufficient free network capacity is available.
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Simulation Validation Of Wireless Sensor Network Linear Resource Reservation Congestion Control Protocol (LRRCCP)

Simulation Validation Of Wireless Sensor Network Linear Resource Reservation Congestion Control Protocol (LRRCCP)

Consequently, the analysis of the performance of these three mechanisms in terms of packet loss ratio, network throughput, average source transmission rate (i.e. average [r]

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Call Admission Control Jointly with Resource Reservation in Cellular Wireless Networks

Call Admission Control Jointly with Resource Reservation in Cellular Wireless Networks

with a threshold ( M ); if the number of new calls does not exceed the threshold, it is admitted; otherwise, it is blocked, while hando ff calls is rejected only when there is no bandwidth in the system. But this scheme assumes that all prioritized and nonprioritized calls require constant bandwidth and reserves constant bandwidth for the delay- tolerant calls, that is, nonprioritized calls. It leads to lack of capacity using for delay-tolerant calls in their upper bound of reserved bandwidth while there is no prioritized call at the system. Without any change in the optimal M threshold number, proposed CAC policy in conjunction with bandwidth reservation, changes the reserved area for the nonprioritized calls dynamically upon each new prioritized call arrival. Admission policy for proposed CAC is given in Algorithm 2.
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