memory consumption
Recently Published Documents


TOTAL DOCUMENTS

247
(FIVE YEARS 123)

H-INDEX

8
(FIVE YEARS 5)

Author(s):  
Anitha Krishna Gowda ◽  
Ananda Babu Jayachandra ◽  
Raviprakash Madenur Lingaraju ◽  
Vinay Doddametikurke Rajkumar

<p><span>Hybrid medium access control (MAC) scheme is one of the prominent mechanisms to offer energy efficiency in wireless sensor network where the potential features for both contention-based and schedule-based approaches are mechanized. However, the review of existing hybrid MAC scheme shows many loopholes where mainly it is observed that there is too much inclusion of time-slotting or else there is an inclusion of sophisticated mechanism not meant for offering flexibility to sensor node towards extending its services for upcoming applications of it. Therefore, this manuscript introduces a novel hybrid MAC scheme which is meant for offering cost effective and simplified scheduling operation in order to balance the performance of energy efficiency along with data aggregation performance. The simulated outcome of the study shows that proposed system offers better energy consumption, better throughput, reduced memory consumption, and faster processing in contrast to existing hybrid MAC protocols.</span></p>


2022 ◽  
Vol 6 (POPL) ◽  
pp. 1-30
Author(s):  
Faustyna Krawiec ◽  
Simon Peyton Jones ◽  
Neel Krishnaswami ◽  
Tom Ellis ◽  
Richard A. Eisenberg ◽  
...  

In this paper, we give a simple and efficient implementation of reverse-mode automatic differentiation, which both extends easily to higher-order functions, and has run time and memory consumption linear in the run time of the original program. In addition to a formal description of the translation, we also describe an implementation of this algorithm, and prove its correctness by means of a logical relations argument.


2022 ◽  
Vol 6 (POPL) ◽  
pp. 1-28
Author(s):  
Michalis Kokologiannakis ◽  
Iason Marmanis ◽  
Vladimir Gladstein ◽  
Viktor Vafeiadis

Dynamic partial order reduction (DPOR) verifies concurrent programs by exploring all their interleavings up to some equivalence relation, such as the Mazurkiewicz trace equivalence. Doing so involves a complex trade-off between space and time. Existing DPOR algorithms are either exploration-optimal (i.e., explore exactly only interleaving per equivalence class) but may use exponential memory in the size of the program, or maintain polynomial memory consumption but potentially explore exponentially many redundant interleavings. In this paper, we show that it is possible to have the best of both worlds: exploring exactly one interleaving per equivalence class with linear memory consumption. Our algorithm, TruSt, formalized in Coq, is applicable not only to sequential consistency, but also to any weak memory model that satisfies a few basic assumptions, including TSO, PSO, and RC11. In addition, TruSt is embarrassingly parallelizable: its different exploration options have no shared state, and can therefore be explored completely in parallel. Consequently, TruSt outperforms the state-of-the-art in terms of memory and/or time.


2021 ◽  
Vol 5 (4) ◽  
pp. 438
Author(s):  
Siti Salwani Binti Yaacob ◽  
Hairulnizam Bin Mahdin ◽  
Mohammed Saeed Jawad ◽  
Nayef Abdulwahab Mohammed Alduais ◽  
Akhilesh Kumar Sharma ◽  
...  

The globalization of manufacturing has increased the risk of counterfeiting as the demand grows, the production flow increases, and the availability expands. The intensifying counterfeit issues causing a worriment to companies and putting lives at risk. Companies have ploughed a large amount of money into defensive measures, but their efforts have not slowed counterfeiters. In such complex manufacturing processes, decision-making and real-time reactions to uncertain situations throughout the production process are one way to exploit the challenges. Detecting uncertain conditions such as counterfeit and missing items in the manufacturing environment requires a specialized set of technologies to deal with a flow of continuously created data. In this paper, we propose an uncertain detection algorithm (UDA), an approach to detect uncertain events such as counterfeit and missing items in the RFID distributed system for a manufacturing environment. The proposed method is based on the hashing and thread pool technique to solve high memory consumption, long processing time and low event throughput in the current detection approaches. The experimental results show that the execution time of the proposed method is averagely reduced 22% in different tests, and our proposed method has better performance in processing time based on RFID event streams.


2021 ◽  
Vol 2132 (1) ◽  
pp. 012032
Author(s):  
Bing Ai ◽  
Yibing Wang ◽  
Liang Ji ◽  
Jia Yi ◽  
Ting Wang ◽  
...  

Abstract Graph neural network (GNN) has done a good job of processing intricate architecture and fusion of global messages, research has explored GNN technology for text classification. However, the model that fixed the entire corpus as a graph in the past faced many problems such as high memory consumption and the inability to modify the construction of the graph. We propose an improved model based on GNN to solve these problems. The model no longer fixes the entire corpus as a graph but constructs different graphs for each text. This method reduces memory consumption, but still retains global information. We conduct experiments on the R8, R52, and 20newsgroups data sets, and use accuracy as the experimental standard. Experiments show that even if it consumes less memory, our model accomplish higher than existing models on multiple text classification data sets.


2021 ◽  
Author(s):  
◽  
Stephen Frank Nelson

<p>Freshly created objects are a blank slate: their mutable state and their constant properties must be initialised before they can be used. Programming languages like Java typically support object initialisation by providing constructor methods. This thesis examines the actual initialisation of objects in real-world programs to determine whether constructor methods support the initialisation that programmers actually perform. Determining which object initialisation techniques are most popular and how they can be identified will allow language designers to better understand the needs of programmers, and give insights that VM designers could use to optimise the performance of language implementations, reduce memory consumption, and improve garbage collection behaviour. Traditional profiling typically either focuses on timing, or uses sampling or heap snapshots to approximate whole program analysis. Classifying the behaviour of objects throughout their lifetime requires analysis of all program behaviour without approximation. This thesis presents two novel whole-program object profilers: one using purely class modification (#prof ), and a hybrid approach utilising class modification and JVM support (rprof ). #prof modifies programs using aspect-oriented programming tools to generate and aggregate data and examines objects that enter different collections to determine whether correlation exists between initialisation behaviour and the use of equality operators and collections. rprof confirms the results of an existing static analysis study of field initialisation using runtime analysis, and provides a novel study of object initialisation behaviour patterns.</p>


2021 ◽  
Author(s):  
◽  
Stephen Frank Nelson

<p>Freshly created objects are a blank slate: their mutable state and their constant properties must be initialised before they can be used. Programming languages like Java typically support object initialisation by providing constructor methods. This thesis examines the actual initialisation of objects in real-world programs to determine whether constructor methods support the initialisation that programmers actually perform. Determining which object initialisation techniques are most popular and how they can be identified will allow language designers to better understand the needs of programmers, and give insights that VM designers could use to optimise the performance of language implementations, reduce memory consumption, and improve garbage collection behaviour. Traditional profiling typically either focuses on timing, or uses sampling or heap snapshots to approximate whole program analysis. Classifying the behaviour of objects throughout their lifetime requires analysis of all program behaviour without approximation. This thesis presents two novel whole-program object profilers: one using purely class modification (#prof ), and a hybrid approach utilising class modification and JVM support (rprof ). #prof modifies programs using aspect-oriented programming tools to generate and aggregate data and examines objects that enter different collections to determine whether correlation exists between initialisation behaviour and the use of equality operators and collections. rprof confirms the results of an existing static analysis study of field initialisation using runtime analysis, and provides a novel study of object initialisation behaviour patterns.</p>


2021 ◽  
Vol 2074 (1) ◽  
pp. 012009
Author(s):  
Yanjing Cai

Abstract Differentiated service for packets entering the network is available through packet matching. Network security and differentiated services mean an inevitable choice for routers. Recursive data flow matching algorithm (RFC) is a high performance packet matching algorithm. However, with the increase of rule dimension and scale in the rule base, system memory consumption is unavoidable. This paper lowers memory consumption via improvement on RFC by dividing the rule base into several subsets and storing each rule in a separate subset. In addition, a variety of methods are used to streamline the RFC data structure for further improvement in algorithm speed and memory performance. The experimental results show that the improved algorithm of RFC greatly reduces the overall memory consumption of RFC, while greatly improving package matching performance.


2021 ◽  
Vol 2111 (1) ◽  
pp. 012054
Author(s):  
M.A. Hamid ◽  
S.A. Rahman ◽  
I.A. Darmawan ◽  
M. Fatkhurrokhman ◽  
M. Nurtanto

Abstract Testing the performance efficiency aspect was carried out to test the performance efficiency of the Unity 3D and Blender-based virtual laboratory media during the COVID-19 pandemic at the Electrical Engineering Vocational Laboratory. This test is carried out to test the performance of the media that has been created. The aspects tested are access speed, process speed, and simulation speed when run. Tests were conducted to measure processor and memory consumption through real time monitoring using MSI Afterburner. Divided into 2 stages of testing, namely time behavior and resource utilization. Time-behavior is focused on how long it takes the media or software to provide a response time to perform an action from a certain function. Resource-utilization is the degree to which software uses some resources when doing something under certain conditions.


Author(s):  
P. Naresh ◽  
R. Suguna

According to recent statistics, there was drastic growth in online business sector where more number of customers intends to purchase items. Due to these retailers accumulates huge volumes of data from day to day operations and engrossed in analyzing the data to watch the behavior of customers at items which strengthen the business promotions and catalog management. It reveals the customer interestingness and frequent items from large data. To carry out this there was known algorithms present which deals with static and dynamic data. Some of them are lag time and memory consuming and involves unnecessary process. This paper intents to implement an efficient incremental pre ordered coded tree (IPOC) generation for data updates and applies frequent item set generation algorithm on the tree. While incremental generation of tree, new data items will link to previous nodes in tree by increasing its support count. This removes the lagging issues in existing algorithms and does not need to mine from scratch and also reduces the time, memory consumption by the use of nodeset data structure. The results of proposed method was observed and analyzed with existing methods. The anticipated method shows improved results by means of generated items, time and memory.


Sign in / Sign up

Export Citation Format

Share Document