{"title":"Thorough Data Pruning for Join Query in Database System","authors":"Gao Jintao;Li Zhanhuai;Sun Jian","doi":"10.1109/TSUSC.2023.3279382","DOIUrl":"10.1109/TSUSC.2023.3279382","url":null,"abstract":"The improvement of robustness and efficiency for multi-way equijoin query is challenging, no-matter for centralized database systems or distributed database systems. Due to lots of unnecessary data existing during query processing, these two metrics will be seriously reduced. If we can thoroughly prune unnecessary data in advance, the robustness and efficiency will be highly improved. However, the pruning power of current strategies, such as predicate push-down and algebraic equivalence, is limited. We present deepDP, a powerful, generalized, and efficient strategy for data pruning. deepDP builds multiple independent pruning spaces by generating longest transitive closures and applies appropriate data pruning strategy for each pruning space. For thoroughly pruning unnecessary data, deepDP employs \u0000<inline-formula><tex-math>$alpha cdot beta$</tex-math></inline-formula>\u0000 pruning strategy to clean each pruning space based on a newly designed statistic information-Hollow Range and re-shuffles the elements in all pruned spaces for maximizing robustness and efficiency benefits meanwhile minimizing the invasion. We implement deepDP in PostgreSQL but are not limited to it, and evaluate deepDP on TPC-H, JOB, and our synthesis benchmark–DHR. The experiment results show that compared to traditional data pruning strategy, deepDP can improve multi-way equijoin query on efficiency by 3.5x.","PeriodicalId":13268,"journal":{"name":"IEEE Transactions on Sustainable Computing","volume":"9 3","pages":"409-421"},"PeriodicalIF":3.9,"publicationDate":"2023-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84036343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Obstacle Adaptive Smooth Path Planning for Mobile Data Collector in the Internet of Things","authors":"Raj Anwit;Prasanta K. Jana;Mohammad S. Obaidat","doi":"10.1109/TSUSC.2023.3281886","DOIUrl":"10.1109/TSUSC.2023.3281886","url":null,"abstract":"In the edge-based Internet of Things (IoT) era, wireless sensor networks (WSNs) are the prime source for data collection. In such WSNs, mobile edge nodes such as mobile sinks (MSs) are the superior means to collect sensed data by visiting rendezvous points (RPs). However, WSNs are often obstacle-ridden, which creates hurdles to the movement of the MSs. Most of the existing path planning works dealing with obstacles do not address optimal and smooth path construction. In other words, they have not considered a) optimizing the number of RPs and constructing a feasible path and b) smoothing the constructed path by considering sharp edges and convexity of the obstacle perimeter. In this paper, we address all such issues and develop an efficient scheme for determining an optimal number of RPs using a greedy approach to the set-cover problem and optimized path construction, both in polynomial time. Then, we apply the modified BUG2 algorithm to construct an obstacle-free path, which is then smoothed using the concept of the Bezier curve. Extensive simulations show the superiority of our proposed scheme over the existing algorithms in terms of energy consumption, latency, and so on.","PeriodicalId":13268,"journal":{"name":"IEEE Transactions on Sustainable Computing","volume":"8 4","pages":"727-738"},"PeriodicalIF":3.9,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75654418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mohsen Ansari;Sepideh Safari;Nezam Rohbani;Alireza Ejlali;Bashir M. Al-Hashimi
{"title":"Power-Efficient and Aging-Aware Primary/Backup Technique for Heterogeneous Embedded Systems","authors":"Mohsen Ansari;Sepideh Safari;Nezam Rohbani;Alireza Ejlali;Bashir M. Al-Hashimi","doi":"10.1109/TSUSC.2023.3282164","DOIUrl":"10.1109/TSUSC.2023.3282164","url":null,"abstract":"One of the essential requirements of embedded systems is a guaranteed level of reliability. In this regard, fault-tolerance techniques are broadly applied to these systems to enhance reliability. However, fault-tolerance techniques may increase power consumption due to their inherent redundancy. For this purpose, power management techniques are applied, along with fault-tolerance techniques, which generally prolong the system lifespan by decreasing the temperature and leading to an aging rate reduction. Yet, some power management techniques, such as Dynamic voltage and frequency scaling (DVFS), increase the transient fault rate and timing error. For this reason, heterogeneous multicore platforms have received much attention due to their ability to make a trade-off between power consumption and performance. Still, it is more complicated to map and schedule tasks in a heterogeneous multicore system. In this paper, for the first time, we propose a power management method for a heterogeneous multicore system that reduces power consumption and tolerates both transient and permanent faults through primary/backup technique while considering core-level power constraint, real-time constraint, and aging effect. Experimental evaluations demonstrate the efficiency of our proposed method in terms of reducing power consumption compared to the state-of-the-art schemes, together with guaranteeing reliability and considering the aging effect.","PeriodicalId":13268,"journal":{"name":"IEEE Transactions on Sustainable Computing","volume":"8 4","pages":"715-726"},"PeriodicalIF":3.9,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72713993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Low-Carbon Mixed Traffic Route Recommendation for Community Residents Based on Multilayer Complex Traffic Network","authors":"Song Wang;Tangyuan Zou;Weixin Zhao;Liang Liu","doi":"10.1109/TSUSC.2023.3271220","DOIUrl":"10.1109/TSUSC.2023.3271220","url":null,"abstract":"With the proposed ”carbon peaking” and ”carbon neutral” goals in China, the transportation sector, as the second largest consumer of oil and a major producer of greenhouse gases, is a critical area for energy efficiency and emission reduction actions. However, few studies have focused on the effective combination of solving residents’ commuting challenges and low-carbon travel. In this paper, by extracting real traffic flow data from taxi and bike-sharing trajectory data, a multilayer complex traffic network is formed to realize an interactive visual exploration of urban traffic patterns. Based on this network a low-carbon travel route recommendation is implemented using a modified genetic algorithm to reduce personal carbon emission and travel costs. Meanwhile, the trip chain level carbon emission estimation method is defined for city streets and recommended routes. With the integration of the above algorithms, a visual analytics system is designed and implemented to support the joint exploration of urban traffic patterns and the street carbon emission distribution, low-carbon mixed traffic route recommendations for inter-community commuting, and optimization of low-carbon recommended routes by adjusting bike stations. Take the taxi and bike-sharing trajectory data in Xiamen, China as an example, an evaluation analysis of the system shows that the method is effective in reducing commuting costs for community residents while reducing personal travel carbon emission.","PeriodicalId":13268,"journal":{"name":"IEEE Transactions on Sustainable Computing","volume":"9 3","pages":"299-314"},"PeriodicalIF":3.9,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72619611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Boosting Research for Carbon Neutral on Edge UWB Nodes Integration Communication Localization Technology of IoV","authors":"Ouhan Huang;Huanle Rao;Zhongyi Zhang;Renshu Gu;Hong Xu;Gangyong Jia","doi":"10.1109/TSUSC.2023.3266729","DOIUrl":"10.1109/TSUSC.2023.3266729","url":null,"abstract":"Reducing carbon emission to improving the economy of fuel vehicle is one of the effective ways to achieve Carbon Neutrality. The Internet of Vehicles (IoV) is a developing technology for deep integration of the Internet of Things (IoT) and transportation. The Industrial Internet of Things (IIoT) can incorporate vehicle information to pinpoint vehicle carbon emissions and provide a foundation for the subsequent carbon-neutral decision-making process. To achieve the precision needs of IoT, however, more than conventional Global Navigation Satellite Systems (GNSS) are required. To achieve carbon emission detection, provide high-precision positioning, and provide a foundation for subsequent carbon-neutral decision-making, it is essential to design a carbon emission detection and positioning system with the capability of vehicle networking. The geographic proximity of edge Ultra Wide Band (UWB) nodes and the merging of various data sources are two methods we suggest employing in this study to increase location accuracy in IIoT situations. After carefully examining the positioning error of the single-edge node and the range error achieved in the UWB communication system, we choose a suitable filtering strategy to enhance single-node accuracy. Following the improvement of single-node accuracy, we fuse the location information of multiple edge nodes using a Weighted Least Squares algorithm in the spatial dimension; in the temporal dimension, we use Extended Kalman filtering to fuse the data over a period of time due to the temporal correlation of inter-node communication. Experimental results demonstrate that our co-localization method, which combines temporal and spatial information, achieves higher localization accuracy in comparison with previous work.","PeriodicalId":13268,"journal":{"name":"IEEE Transactions on Sustainable Computing","volume":"9 3","pages":"341-353"},"PeriodicalIF":3.9,"publicationDate":"2023-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87377894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Baixuan Wu;Zheng Xiao;Peiying Lin;Zhuo Tang;Kenli Li
{"title":"Critical Path Awareness Techniques for Large-Scale Graph Partitioning","authors":"Baixuan Wu;Zheng Xiao;Peiying Lin;Zhuo Tang;Kenli Li","doi":"10.1109/TSUSC.2023.3263172","DOIUrl":"https://doi.org/10.1109/TSUSC.2023.3263172","url":null,"abstract":"Graph partitioning is one of the fundamental problems in many graph-based applications and systems. It enables the division of a graph into smaller sub-graphs for subsequent parallel processing, reducing the processing latency of the graph. The critical path of a graph is the logical path with the longest delay from input to output. The processing time of the graph mainly depends on the delay incurred by the critical path, independent of other paths with small delays. Therefore, it can reduce the processing time of the graph by protecting the critical path of the graph from partition. However, existing approaches to graph partitioning only focus on metrics such as minimum cut and partition balance. As a result, the critical paths of graphs may be destroyed in the partitioning procedure. To address this problem, we present a critical path awareness approach, namely path-metis, to protect the critical paths and alleviate the processing latency after graph partitioning. In path-metis, two efficient strategies, including Slack and critical path fix strategies, are introduced. The Slack strategy, which incorporates critical path information into the weights of DAG, is used as pre-processing before traditional multi-level partitioning methods, like Metis. Then, for the generated partitioning scheme, the critical path fix strategy is proposed to further protect critical paths from being cut. We demonstrate the effectiveness of our approach on both real and synthetic datasets. From the experimental results, compared to Metis, our method improves critical path performance by 17.70%.","PeriodicalId":13268,"journal":{"name":"IEEE Transactions on Sustainable Computing","volume":"8 3","pages":"412-422"},"PeriodicalIF":3.9,"publicationDate":"2023-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50280160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Data Center Sustainability: Revisits and Outlooks","authors":"Zhiwei Cao;Xin Zhou;Xiangyu Wu;Zhaomeng Zhu;Tracy Liu;Jeffery Neng;Yonggang Wen","doi":"10.1109/TSUSC.2023.3281583","DOIUrl":"10.1109/TSUSC.2023.3281583","url":null,"abstract":"As energy-intensive entities, data centers are associated with significant environmental impacts, making their sustainability a subject of growing interest in recent years. In this article, we revisit data center sustainability and propose a forward-looking vision for improving data center sustainability. We argue that data center sustainability encompasses more than just energy efficiency and must be evaluated and optimized through a multi-faceted approach. To this end, we first present an overview of the sustainability metrics from five aspects. After that, we demonstrate the sustainability status of the latest data centers utilizing publicly available data center sustainability ratings. Furthermore, we examine the evolution of data center sustainability standards in Singapore to highlight several trending features. Based on the analysis, we identify several key elements of sustainable data centers. We then propose the Cognitive Digital Twin (CDT) architecture, which incorporates a digital twin engine for system-wide simulation and a decision engine for optimal control to improve data center sustainability. A case study is performed to optimize the chiller plant efficiency of a production data center in Singapore. The results demonstrate that the CDT can improve chiller plant energy efficiency by 5%, indicating around 140 metric tons of annual carbon emission savings.","PeriodicalId":13268,"journal":{"name":"IEEE Transactions on Sustainable Computing","volume":"9 3","pages":"236-248"},"PeriodicalIF":3.9,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88809223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xinghao Yang;Yongshun Gong;Weifeng Liu;James Bailey;Dacheng Tao;Wei Liu
{"title":"Semantic-Preserving Adversarial Text Attacks","authors":"Xinghao Yang;Yongshun Gong;Weifeng Liu;James Bailey;Dacheng Tao;Wei Liu","doi":"10.1109/TSUSC.2023.3263510","DOIUrl":"https://doi.org/10.1109/TSUSC.2023.3263510","url":null,"abstract":"Deep learning models are known immensely brittle to adversarial text examples. Existing text adversarial attack strategies can be roughly divided into character-level, word-level, and sentence-level attacks. Despite the success brought by recent text attack methods, how to induce misclassification with minimal text modifications while keeping the lexical correctness, syntactic soundness, and semantic consistency is still a challenge. In this paper, we devise a Bigram and Unigram-based adaptive Semantic Preservation Optimization (BU-SPO) approach which attacks text documents not only at a unigram word level but also at a bigram level to avoid generating meaningless sentences. We also present a hybrid attack strategy that collects substitution words from both synonyms and sememe candidates, to enrich the potential candidate set. Besides, a Semantic Preservation Optimization (SPO) method is devised to determine the word substitution priority and reduce the perturbation cost. Furthermore, we constrain the SPO with a semantic Filter (dubbed SPOF) to improve the semantic similarity. To estimate the effectiveness of our proposed methods, BU-SPO and BU-SPOF, we attack four victim deep learning models trained on three text datasets. Experimental results demonstrate that our approaches accomplish the highest semantics consistency and attack success rates by making minimal word modifications compared with competitive methods.","PeriodicalId":13268,"journal":{"name":"IEEE Transactions on Sustainable Computing","volume":"8 4","pages":"583-595"},"PeriodicalIF":3.9,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138558208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"EAQ: Enabling Authenticated Complex Query Services in Sustainable-Storage Blockchain","authors":"Bo Yin;Weilong Zeng;Peng Zhang;Xuetao Wei","doi":"10.1109/TSUSC.2023.3263232","DOIUrl":"https://doi.org/10.1109/TSUSC.2023.3263232","url":null,"abstract":"The data query service is urgently required in sustainable-storage blockchain, where full nodes store the entire transaction data while light nodes only store block headers. Queries invariably seek data with multiple attributes. However, no existing method provides a unified authenticated data structure (ADS) to support complex query operators (e.g., range queries and data object queries) on multiattribute blockchain data. In this paper, we propose a framework EAQ that effectively supports both fast data queries on multiple attributes and authentication of the query result. We propose a new ADS, called the MR\u0000<inline-formula><tex-math>$^{Bloom}$</tex-math></inline-formula>\u0000-tree, based on the Bloom filter (BF) and Merkle R-tree. We prove the decomposability of BFs, which enables the BF to be seamlessly incorporated with the Merkle R-tree. This ADS enables range-level search using multidimensional attribute ranges and object-level search using BFs. This ADS also supports querying and proving inexistent data objects. To reduce storage overhead, we improve the MR\u0000<inline-formula><tex-math>$^{Bloom}$</tex-math></inline-formula>\u0000-tree using the suppressed BF structure, which constructs only one BF independent of the number of attributes. To manage string attributes, we transform them into discrete numerical attributes using density-based clustering to represent similar items with close numerical values. Experiments show that the proposed framework achieves promising results.","PeriodicalId":13268,"journal":{"name":"IEEE Transactions on Sustainable Computing","volume":"8 3","pages":"435-447"},"PeriodicalIF":3.9,"publicationDate":"2023-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50400595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An Effective Optimal Economic Sustainable Clean Energy Solution With Reduced Carbon Capturing/Carbon Utilization/ Carbon Footprint for Grid Integrated Hybrid System","authors":"Abhinav Saxena;Aseem Chandel;Amit Kumar Dash;Shailendra Kumar Gupta;Sampath Kumar V;J. P. Pandey","doi":"10.1109/TSUSC.2023.3262982","DOIUrl":"https://doi.org/10.1109/TSUSC.2023.3262982","url":null,"abstract":"The integration of conventional sources with the grid has many challenges, like carbon emission, optimal cost of the system, and power quality issues. All these shortcomings create a non-sustainability in the environment, which is of great concern. In order to overcome such issues, a hybrid system is designed that is composed of various components or sources like wind energy, solar photovoltaic energy, thermal energy, and battery energy storage with the purpose of providing an environmentally friendly, economically viable, sustainable, and reliable solution. The objective is to reduce the carbon capture, carbon utilization, and carbon footprint. The carbon footprint is measured as the optimal difference between carbon capture (CC) and its utilization (CU), and carbon emission is represented as loss of carbon emission (LCE). Another objective is to reduce the optimal size of components, the distortion level, and the optimal cost in terms of loss of cost of energy (LCOE) for the various values of loss of power supply probability (LPSP). All the above objectives are accomplished by designing a nonlinear multi-objective problem. The designed nonlinear multi-objective function is based on a hybrid hysteresis fuzzy algorithm. The proposed algorithm is a combination of both fuzzy logic controllers and the hysteresis band method. The effectiveness of the proposed topology is tested on an IEEE standard 9 bus system. It is observed that a nonlinear hybrid hysteresis fuzzy algorithm provides a reliable and sustainable solution for optimal cost with a reduced effective carbon footprint and minimal distortion by maintaining the proper balance between carbon capturing and carbon utilization. The average values of LCOE,LCE, CU, and CC with the proposed method for various LPSP are found to be 0.5926 $/KWh, 70.64 g CO2/kWh, 89 g CO2/kWh, and 159 g CO2/kWh, which are the least among all methods.","PeriodicalId":13268,"journal":{"name":"IEEE Transactions on Sustainable Computing","volume":"8 3","pages":"385-399"},"PeriodicalIF":3.9,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50400596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}