ance mechanisms implemented in the transport layer protocol like TCP to provide good service under heavy load. If network nodes distribute bandwidth fairly, the Internet would be more robust and accommodate a wide variety of applications. Various congestion and bandwidth management schemes have been proposed for this purpose and can be classified into two broad categories: Packet scheduling algorithms such as Fair Queueing (FQ ) which explicitly provide bandwidth shares by scheduling packets. They are more difficult to implement compared to FIFO queueing. The second category has active queue management schemes such as RED  which use FIFO queues at the routers. They are easy to implement but don’t aim to provide (and, in the presence of non-congestion- responsive sources, don’t provide) fairness. An algorithm called AFD (Approximate Fair Dropping) ), has been proposed to provide approximate, weighted max-min fairbandwidth allocations with relatively low complexity. AFD has since been widely adopted by the industry. This paper describes the evolution of AFD from a research project into an industry setting, focusing on the changes it has undergone in the process. AFD now serves as a traffic management module, which can be implemented either using a single FIFO or overlaid on top of extant per-flow queueing structures and which provides approximate bandwidth allocation in a simple fashion.
We investigate the problem of providing a fairbandwidth allocation to each of flows that share the outgoing link of a congested router. The buffer at the outgoing link is a simple FIFO, shared by packets belonging to the flows. We devise a simple packet dropping scheme, called CHOKe-FS that discriminates against the flows which submit more packets/sec than is allowed by their fair share. By doing this, the scheme aims to approximate the fair queueing policy
Abstract–Hundreds of thousands of servers from data centers are operated to provide users with pay-as-you- go infrastructure as a service, platform as a service, and software as a service. Many different types of virtual machine (VM) instances hosted on these servers oftentimes need to efficiently communicate with data movement under current bandwidth capacity. This motivates providers to seek for a bandwidth scheduler to satisfy objectives, namely assuring the minimum bandwidth per VM for the guaranteed deadline and eliminating network congestion as much as possible. Based on some rigorous mathematical models, we formulated a cloud-based bandwidth scheduling algorithm which enables dynamic and fairbandwidth management by categorizing the total bandwidth into several categories and adjusting the allocated bandwidth limit per VM for both upstream and downstream traffics in real time. The simulation showed that paradigm was able to utilize the total assigned bandwidth more efficiently compared to algorithms such as bandwidth efficiency persistence proportional sharing (PPS), PPS, and PS at the network level.
(b) Packet drops
Fig. 3. Small average queue size and zero packet drops are achieved for the 155Mb/s link in Figure 1
The simulation scenarios include multiple bottleneck topologies, heterogeneous RTTs, and web-like traffic. There are two key questions we aim to answer: 1) does iXCP fix the problem of XCP and achieve max-min fair allocation? 2) does iXCP make other properties of XCP worse? To answer the first question, we compute two metrics: 1) link utilization; 2) a flow’s rate normalized by its theoretical max-min rate. If the link utilization is 100%, and a flow’s normalized rate is 1, it shows that iXCP achieves max-min fairbandwidth allocation. To answer the second question, we examine three metrics: 1) the persistent queue sizes; 2) the packet drops; 3) the convergence speed when flows join and leave the network.
WiMAX has been recently labeled as one of the few contending technologies for next generation of wireless networks. Among the other features of this technology, QoS and Radio Resource Management are the topics on which maximum research is being done. Many research groups have proposed schemes for physical slot, call admission and control, and bandwidth allocation strategies. Scheduling is the heart of QoS for WiMAX networks. The throughput of uplink or downlink is proportional to the number of subcarriers allocated to the corresponding SS and the achievable rate of each subcarrier . WiMAX standard IEEE 802.16e supports five service classes namely, UGS, ertPS, rtPS, nrtPS and BE. All of these classes have different QoS requirements. Considering the QoS requirements and the mobility of users in the coverage area with variable channel status, allocation of resources in fair manner and efficiently is a complex issue [11, 12]. The objective of WiMAX scheduling is to ensure that the QoS requirements for all the five classes are met efficiently. In order to make sure that this requirement of different service classes is met, several researchers have came up with different algorithms.  Apart from the commonly used techniques in WiMAX, mobile WiMAX IEEE 802.16e used some special techniques which are dependent upon quality of signal. The parameters used here are temporal fairness and throughput fairness.  The QoS in WiMAX is dependent upon better and optimized scheduling algorithms, the modulation scheme used needs to be selected along with the code rate . Since the discovery of wireless networks, scheduling for resource allocation has always been a major point of research . The main task of the scheduler is to maintain desired levels of QoS, fairness and throughput of the network. To achieve QoS and fairness, researchers have constantly worked upon several scheduling algorithms from different computing backgrounds and studied their implementation and effect on network performance . For the sake of better understanding of the problem and analyzing various theories available, the types of schedulers can be classified into four different categories which are as follows:
This paper introduced a utility-maximization model for fairbandwidth sharing between virtual networks in VDCs to provide multi tenants mechanism for network resource under cloud computing. In the model, every physical link is associated with a fairness index constraint in maximize utility calculating. The goal is to limit the differences among the bandwidth allocation of the virtual links which share the same physical link. In our future work, we will test the trade-off between fairness and the bandwidth utilizing rate under some conditions such as not all virtual networks need bandwidth guarantee, i.e. the dynamic bandwidth allocation taking into account the fairness. References
7. Conclusion and future work
Motivated by a need for efficient AQM algo- rithms for the internet, we have proposed FABA, a rate control based AQM discipline that is well suited to network edges or gateways (e.g., the ISPs). FABA achieves a fairbandwidth allocation amongst competing flows with a mix of adaptive and non-adaptive traffic. It is a congestion avoid- ance algorithm with low implementation over- heads. FABA can be used to partition bandwidth amongst different flows in proportion to pre- assigned weights. It is well suited for bandwidth allocation among flow aggregates as well as for bandwidth sharing within a hierarchy as required in the differentiated services framework. FABA can serve as a useful method for enforcing SLAs in the network. We showed that FABA is Oð1Þ in the amortized sense (and also in the worst case as noticed empirically), whereas the space complexity of FABA is OðBÞ where B is the size (in packets) of the bottleneck buffer. Through simulations, we have compared FABA with other well known congestion avoidance algorithms and have seen that FABA gives superior performance. FABA is
Only Becchetti and Adriani (2002) have a comprehensive analytical model of FT that considers the role of consumers willing to pay a premium for FT products. In their model, Northern consumers can obtain higher utility from a good if they consider it to be “fairly” produced in the South and it is produced in the South by a monopsonist that can choose to pay workers their marginal product (MP - a “fair” wage) or less (“unfair”) and by a FT firm that always pays MP. They argue that, if consumers have “inter- national equality concerned” preferences and there is “efficient rationing” (in the sense that the FT firm can allocate its jobs to those workers with the lowest reservation wages), then equilibrium involves both types of firms paying MP to their workers whereas, with no FT firm (but unchanged pref- erences) the monopsonist would pay less than MP. This occurs because the FT firm hires those workers with the lowest outside options, thereby forcing the monopsonist to pay more than it otherwise would. However, in contrast to the present paper, Becchetti and Adriani do not model the cooperative nature of FT production and nor is there any responsiveness of consumer welfare to the level of Southern wages: the good is simply considered to be fairly produced or not.
I can congratulate myself for not buying cocoa produced by slaves, but my purchases of fairly traded cocoa do not help to bring the [modern] slave trade to an end, because they don’t prevent other people from buying cocoa whose production depends on slavery. This is not to say that voluntary fair trade is pointless—it has distributed wealth to impoverished people—simply that, while it encourages good practice, it does not discourage bad practice.
account, it is impossible to see how the question could even be answered. Sher defines a lottery, after all, as a tiebreaking device; this implies that a coin tossed in order to break a tie might count as a fair lottery, whereas the exact same coin tossed for some other purpose does not. This result is counterintuitive. Admittedly, lotteries might reasonably be defined in terms of their use, just as with other tools (hammers, etc.). But the definition of a tool should not depend on its actual use for that purpose. A hammer is something useful for pounding nails into wood, but it remains a hammer even when it is not being used for this purpose. Similarly, a lottery (fair or otherwise) is a procedure that can be used to break ties, but it remains a lottery even when it is not being so used. By tying the definition of a lottery so closely to actual use, Sher introduces another irrelevant factor into the process of distinguishing fair lotteries.
renovation/rehabilitation; or original construction completion. Long-term renovations should not exceed six (6) months and then occupied within sixty (60) days of completion.
Due to the vacancy hazard, the Plan would typically require a twenty (20) day wait, no
vandalism coverage, and a higher than normal deductible. Policy surcharges are available for use in the case of a vacancy hazard. The property must be secured from unauthorized entry. The FAIR Plan reserves the right to cancel a policy for misrepresentation during the vacancy period if the actual renovation progress falls short of the estimates provided by the applicant at the time of application. If requested, the Association will waive the waiting period for a real estate closing with full payment and photographs of the property.
bandwidth. For both LAN and WAN links, you can verify that the network can support a given data rate or you can determine the maximum data rate for a network link. You can observe how changes in the network hardware, software or configuration affect throughput. You can see how different traffic types and traffic loads impact throughput. You can plot throughput rates over time to gain a more thorough understanding of network performance and health.
You can see the current bandwidth used in each queue by choosing Status/Queues from the pfSense menu, which will give you a page like this:
Note that the Queue Length will vary as the TCP streams try to adjust their speed to the amount allocated by the traffic shaping. Every dropped packet will cause a TCP stream to reduce its speed, and cause the queue length to drop. The TCP stream will then try to adjust its speed slowly upwards, searching for the limit again. When the speed is higher than the allocated bandwidth, the queue will lengthen. When it becomes full again, another packet will drop and the speed will be reduced again. This process repeats as long as the TCP stream is running, like this:
We study the following multiagent variant of the knapsack problem. We are given a set of items, a set of voters, and a value of the budget; each item is endowed with a cost and each voter assigns to each item a certain value. The goal is to select a subset of items with the total cost not exceeding the budget, in a way that is consistent with the voters’ pref- erences. Since the preferences of the voters over the items can vary significantly, we need a way of aggregating these preferences, in order to select the socially best valid knap- sack. We study three approaches to aggregating voters’ pref- erences, which are motivated by the literature on multiwin- ner elections and fair allocation. This way we introduce the concepts of individually best, diverse, and fair knapsack. We study the computational complexity (including parameterized complexity, and complexity under restricted domains) of the aforementioned multiagent variants of knapsack.