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Many applications extensively use data objects with a regular and fixed layout, which leads to the recurrence of access patterns over memory regions. Spatial data prefetching techniques exploit this phenomenon to prefetch future memory references and hide their long latency. Spatial prefetchers are particularly of interest because they usually only need a small storage budget. In this chapter, we introduce the concept of spatial prefetching and present two instances of spatial data prefetchers, SMS and VLDP. © 2021 Elsevier Inc  

Applications extensively use data objects with a regular and fixed layout, which leads to the recurrence of access patterns over memory regions. Spatial data prefetching techniques exploit this phenomenon to prefetch future memory references and hide the long latency of DRAM accesses. While state-of-the-art spatial data prefetchers are effective at reducing the number of data misses, we observe that there is still significant room for improvement. To select an access pattern for prefetching, existing spatial prefetchers associate observed access patterns to either a short event with a high probability of recurrence or a long event with a low probability of recurrence. Consequently, the... 

Monthly mean satellite derived Chl-a, aerosols, wind, SST, PAR, and turbidity datasets were used to investigate the possible factors regulating phytoplankton variability in the Persian Gulf. The spatial correlation analysis revealed two distinct regions of SST and PAR, and a relatively uniform spatial correlation pattern of the other parameters. The cross correlation between aeolian dusts and Chl-a was significantly positive with 1–3 months offset. The pattern of spatial correlation between Chl-a and SST was positive in the shallow regions without time lag, and was negative with time offset of 3–5 months in deeper regions. The cross correlation between Chl-a and north-ward winds were... 

In this article, the relation between meteorological parameters and dust activities in western Iran has been studied. Satellite-based data achieved from TOMS are used to investigate the dust activities within a time period of 30 years. In the first part of this study, we examine the statistical trend of Aerosol Index (AI) and local meteorological parameters in 15 different stations. The same patterns of AI variations in all stations indicate that this region has always been subjected to dust storms which originate from similar sources in the neighboring countries that could be known as a sole dust transfer system. In the second part, we investigate the spatial correlation between the... 

According to crash configuration and pre-crash conditions, traffic crashes are classified into different collision types. Based on the literature, multi-vehicle crashes, such as head-on, rear-end, and angle crashes, are more frequent than single-vehicle crashes, and most often result in serious consequences. From a methodological point of view, the majority of prior studies focused on multivehicle collisions have employed univariate count models to estimate crash counts separately by collision type. However, univariate models fail to account for correlations which may exist between different collision types. Among others, multivariate Poisson lognormal (MVPLN) model with spatial correlation... 

Spectrum sensing is the basic step in cognitive radio networks. Its accuracy directly affects spectrum utilization. In this paper we propose a new method for blind cooperative spectrum sensing using spatial information. We model our sensing matrix as a graph, taking advantage of signal and spatial correlation of antennas. We prove that the general settings of the problem are hard to approximate. Taking spatial information into account, we propose a new scheme to find white space subregions. Cognitive radio users residing in the region may be able to transmit, but must keep their transmission power to the extent that no interference is caused to primary receivers out of the region  

Data aggregation is an effective technique which is introduced to conserve energy by reducing packet transmissions in wireless sensor networks (WSNs). In addition, it is possible to consume less energy by using the spatial correlation and redundancy of data in dense networks to form clusters of nodes sensing similar values and, in turn, transmit one data packet per cluster. In this paper, we propose a Data-Aware Clustering and Aggregation scheme (DACA) to manage the energy constraint in a query-driven WSN. The DACA selects cluster head nodes by forming a new factor as a function of three parameters including the residual energy, the data value, and the number of neighbors at each node.... 

A significant challenge in spectrum sensing is to lessen the signal to noise ratio needed to detect the presence of primary users while the noise level may also be unknown. To meet this challenge, multi-antenna based techniques possess a greater efficiency compared to other algorithms. In a typical compact multi-antenna system, due to small interelement spacing, mutual coupling between thermal noises of adjacent receivers is significant. In this paper, unlike most of the spectrum sensing algorithms which assume spatially uncorrelated noise, the noises on the adjacent antennas can have arbitrary correlations. Also, in contrast to some other algorithms, no prior assumption is made on the... 

Power and bandwidth constraints are two major challenges in wireless sensor networks. Since a considerable amount of energy in sensor networks is consumed for data transmission, compression techniques may prolong the life of such networks. Moreover, with fewer bits to transmit, the network can cope better with the problem of inadequate bandwidth. In this paper, we consider an image sensor network and propose a paradigm based on the principles of Distributed Source Coding (DSC) for efficient compression. Our method relies on high correlation between the sensor nodes. The algorithm consists of two phases: the Training Phase and the Main Phase. In the Training Phase an aggregation node or a... 

We consider the non-cooperative multiple access relay channel, where N users transmit their information to a common receiver with the assistance of a shared relay. For N = 2 independent sources and dual-frequency operation (i.e. two separate frequency channels are available for transmission), it has been recently shown [1, 2] that additional diversity gain can be attained by simply switching the transmit frequency bands between users at the relay site, thus reducing the scenario to a 2 × 2 MIMO channel with achievable diversity order equal to 2. In this paper we propose to extend this previous work to the case where the sources are spatially correlated. Under a Detect-and-Forward (DF) relay... 

Leakage power has already become the major contributor to the total on-chip power consumption, rendering its estimation a necessary step in the IC design flow. The problem is further exacerbated with the increasing uncertainty in the manufacturing process known as process variability. We develop a method to estimate the variation of leakage power in the presence of both intra-die and inter-die process variability. Various complicating issues of leakage prediction such as spatial correlation of process parameters, the effect of different input states of gates on the leakage, and DIBL and stack effects are taken into account while we model the simultaneous variability of the two most critical...