Spatial Big Data and Moving Objects: A Comprehensive Survey <s> 4) OTHER IMPORTANT ROUTING ALGORITHMS FOR VARIOUS NETWORKS <s> With the growing popularity of big-data applications, Data Center Networks increasingly carry larger and longer traffic flows. As a result of this increased flow granularity, static routing cannot efficiently load-balance traffic, resulting in an increased network contention and a reduced throughput. Unfortunately, while adaptive routing can solve this load-balancing problem, network designers refrain from using it, because it also creates out-of-order packet delivery that can significantly degrade the reliable transport performance of the longer flows. In this paper, we show that by throttling each flow bandwidth to half of the network link capacity, a distributed-adaptive-routing algorithm is able to converge to a non-blocking routing assignment within a few iterations, causing minimal out-of-order packet delivery. We present a Markov chain model for distributed-adaptive-routing in the context of Clos networks that provides an approximation for the expected convergence time. This model predicts that for full-link-bandwidth traffic, the convergence time is exponential with the network size, so out-of-order packet delivery is unavoidable for long messages. However, with half-rate traffic, the algorithm converges within a few iterations and exhibits weak dependency on the network size. Therefore, we show that distributed-adaptive-routing may be used to provide a scalable and non-blocking routing even for long flows on a rearrangeably-non-blocking Clos network under half-rate conditions. The proposed model is evaluated and approximately fits the abstract system simulation model. Hardware implementation guidelines are provided and evaluated using a detailed flit-level InfiniBand simulation model. These results directly apply to adaptive-routing systems designed and deployed in various fields. <s> BIB001 </s> Spatial Big Data and Moving Objects: A Comprehensive Survey <s> 4) OTHER IMPORTANT ROUTING ALGORITHMS FOR VARIOUS NETWORKS <s> An ad hoc network is a collection of wireless mobile nodes dynamically forming a temporary network without the use of any existing network infrastructure or centralized administration. Routing in ad-hoc network is a challenging issue. Big data analytics have been suggested for proper evaluation and decision making in routing and placement of ad hoc network nodes. This Paper analyses the performance of AODV and DSR routing protocols for the quality assurance metrics. The performance differentials of AODV and DSR protocols are analyzed using NS-2 which is the main network simulator, NAM (Network Animator) and compared in terms of scales applied on Packet Delivery Ratio (PDR), in different environments specified by varying pause time, speed and number of nodes. <s> BIB002 </s> Spatial Big Data and Moving Objects: A Comprehensive Survey <s> 4) OTHER IMPORTANT ROUTING ALGORITHMS FOR VARIOUS NETWORKS <s> Data centers (DCs), owing to the exponential growth of Internet services, have emerged as an irreplaceable and crucial infrastructure to power this ever-growing trend. A DC typically houses a large number of computing and storage nodes, interconnected by a specially designed network, namely, DC network (DCN). The DCN serves as a communication backbone and plays a pivotal role in optimizing DC operations. However, compared to the traditional network, the unique requirements in the DCN, for example, large scale, vast application diversity, high power density, and high reliability, pose significant challenges to its infrastructure and operations. We have observed from the premium publication venues (e.g., journals and system conferences) that increasing research efforts are being devoted to optimize the design and operations of the DCN. In this paper, we aim to present a systematic taxonomy and survey of recent research efforts on the DCN. Specifically, we propose to classify these research efforts into two areas: 1) DCN infrastructure and 2) DCN operations. For the former aspect, we review and compare the list of transmission technologies and network topologies used or proposed in the DCN infrastructure. For the latter aspect, we summarize the existing traffic control techniques in the DCN operations, and survey optimization methods to achieve diverse operational objectives, including high network utilization, fair bandwidth sharing, low service latency, low energy consumption, high resiliency, and etc., for efficient DC operations. We finally conclude this survey by envisioning a few open research opportunities in DCN infrastructure and operations. <s> BIB003
Beside the algorithms presented so far, there are some important research efforts on routing of BD which are worth mentioning here. For example, the work presented in BIB002 considers analysis of BD traffic generated in MANETs using quality assurance metrics (such as functionality and usability of data). Big data carried by the traditional DSR (dynamic source routing) and AODV (ad hoc on demand distance vector) routing protocols has been simulated using NS2 (network simulator 2). Results depict that AODV performs better than DSR when combined with BD analytics. Moreover, another work presented in BIB001 examines the BD traffic in DCN (data center networks) BIB003 . The authors tackle a challenging task of determining the conditions in which the traditional routing algorithms can carry BD packets with less loss and high throughput. Thus, Markov chains are used for system analysis and probability estimations. Later, through simulations, it is shown that the time taken to reach a ''non-blocking routing'' situation is exponential. In addition, the proposed Markov model achieves a good convergence rate over a DCN of large number of nodes due to its simplicity in signaling. This signaling is named as EAR (explicit adaptation requests) in BIB001 and is performed between various switches to control the packet flow.