Decentralized systems built around blockchain technology promise clients an immutable ledger. They add a transaction to the ledger after it undergoes consensus among the replicas that run a Proof-of-Stake (PoS) or Byzantine Fault-Tolerant (BFT) consensus protocol. Unfortunately, these protocols face a long-range attack where an adversary having access to the private keys of the replicas can rewrite the ledger. An existing solution to this problem forces each committed block from these protocols to undergo another consensus, Proof-of-Work (PoW) consensus; POW protocol wastes computational resources as miners compete to solve complex puzzles. In this paper, we present the design of our Power-of-Collaboration (POC) protocol, which guards existing POS/BFT blockchains against long-range attacks and requires miners to collaborate rather than compete. POC guarantees fairness and accountability and only marginally degrades the throughput of the underlying system.
Dakai Kang, Sajjad Rahnama, Jelle Hellings, Mohammad Sadoghi
The emergence of blockchain technology has renewed the interest in consensus-based data management systems that are resilient to failures. To maximize the throughput of these systems, we have recently seen several prototype consensus solutions that optimize for throughput at the expense of overall implementation complexity, high costs, and reliability. Due to this, it remains unclear how these prototypes will perform in real-world environments. In this paper, we present SPOTLESS, a novel concurrent rotational consensus protocol made practical. Central to SPOTLESS is the combination of (1) a chained rotational consensus design for replicating requests with a reduced message cost and low-cost failure recovery that eliminates the traditional complex, error-prone view-change protocol; (2) the novel Rapid View Synchronization protocol that enables SPOTLESS to work in more general network assumptions, without a need for a Global Synchronization Time to synchronize view, and recover valid earlier views with the aid of non-faulty replicas without the need to rely on the primary; (3) a high-performance concurrent consensus architecture in which independent instances of the chained consensus operate concurrently to process requests with high throughput, thereby avoiding the bottlenecks seen in other rotational protocols. Due to the concurrent consensus architecture, SPOTLESS greatly outperforms traditional primary-backup consensus protocols such as PBFT (by up to 430%), NARWHAL-HS (by up to 137%), and HOTSTUFF (by up to 3803%). Due to its reduced message cost, SPOTLESS is even able to outperform RCC, a state-of-the-art high-throughput concurrent consensus protocol, by up to 23%. Furthermore, SPOTLESS is able to maintain a stable and low latency and consistently high throughput even during failures.
Tayyaba Noreen, Qiufen Xia, Muhammad Zeeshan Haider
In the past decade, blockchain has emerged as a promising solution for building secure distributed ledgers and has attracted significant attention. However, current blockchain systems suffer from limited throughput, poor scalability, and high latency. Due to limitations in consensus mechanisms, especially in managing node identities, blockchain is often considered unsuitable for applications such as the Internet of Things (IoT). This paper proposes the Advanced DAG-based Ranking (ADR) protocol to enhance blockchain scalability and throughput. ADR employs a directed acyclic graph (DAG) structure where nodes are positioned based on their rankings. Unlike traditional chains, ADR allows honest nodes to write blocks and verify transactions using a DAG-based topology. The protocol follows a three-step approach to secure the network against double-spending and enhance performance. First, it verifies nodes using their public and private keys before granting entry. Second, it builds an advanced DAG ledger enabling block production and transaction validation. Third, a ranking algorithm filters out malicious nodes, ranks the remaining nodes based on performance, and arranges them topologically. This process increases throughput and ensures robust scalability. We evaluated ADR on Amazon EC2 clusters with over 100 nodes, including scenarios with injected malicious nodes. Simulation results demonstrate that ADR significantly improves transaction throughput and network liveness compared to existing DAG-based blockchains such as IOTA and ByteBall, making it well-suited for IoT applications.
The scalability problem has been one of the most significant barriers limiting the adoption of blockchains. Blockchain sharding is a promising approach to this problem. However, the sharding mechanism introduces a significant number of cross-shard transactions, which are expensive to process. This paper focuses on the transaction allocation problem to reduce the number of cross-shard transactions for better scalability. In particular, we systematically formulate the transaction allocation problem and convert it to the community detection problem on a graph. A deterministic and fast allocation scheme TxAllo is proposed to dynamically infer the allocation of accounts and their associated transactions. It directly optimizes the system throughput, considering both the number of cross-shard transactions and the workload balance among shards. We evaluate the performance of TxAllo on an Ethereum dataset containing over 91 million transactions. Our evaluation results show that for a blockchain with 60 shards, TxAllo reduces the cross-shard transaction ratio from 98% (by using traditional hash-based allocation) to about 12%. In the meantime, the workload balance is well maintained. Compared with other methods, the execution time of TxAllo is almost negligible. For example, when updating the allocation every hour, the execution of TxAllo only takes 0.5 seconds on average, whereas other concurrent works, such as BrokerChain (INFOCOM'22) leveraging the classic METIS method, require 422 seconds.
Blockchain has been touted as a revolutionary technology. However, despite the excitement, blockchain has not been adopted in many fields. Many are hesitant to adopt blockchain technology due to privacy concerns, barriers to use, or lack of practical use cases. In this work, we outline a potential blockchain use case for tracking financial transactions across multiple financial institutions. We show the downsides of traditional centralized approaches and that blockchain approaches fail to give all the privacy and accessibility required for this use case. Thus we propose a novel blockchain architecture to support our use case. This novel architecture combines the ease of use of public blockchains with the privacy of private blockchains by allowing users to create personal blockchains. We believe this novel personal blockchain architecture will lead to more blockchain adoption, particularly in use cases handling private data.
Private blockchain as a replicated transactional system shares many commonalities with distributed database. However, the intimacy between private blockchain and deterministic database has never been studied. In essence, private blockchain and deterministic database both ensure replica consistency by determinism. In this paper, we present a comprehensive analysis to uncover the connections between private blockchain and deterministic database. While private blockchains have started to pursue deterministic transaction executions recently, deterministic databases have already studied deterministic concurrency control protocols for almost a decade. This motivates us to propose Harmony, a novel deterministic concurrency control protocol designed for blockchain use. We use Harmony to build a new relational blockchain, namely HarmonyBC, which features low abort rates, hotspot resiliency, and inter-block parallelism, all of which are especially important to disk-oriented blockchain. Empirical results on Smallbank, YCSB, and TPC-C show that HarmonyBC offers 2.0x to 3.5x throughput better than the state-of-the-art private blockchains.
Traditional education has been updated with the development of information technology in human history. Within big data and cyber-physical systems, the Metaverse has generated strong interest in various applications (e.g., entertainment, business, and cultural travel) over the last decade. As a novel social work idea, the Metaverse consists of many kinds of technologies, e.g., big data, interaction, artificial intelligence, game design, Internet computing, Internet of Things, and blockchain. It is foreseeable that the usage of Metaverse will contribute to educational development. However, the architectures of the Metaverse in education are not yet mature enough. There are many questions we should address for the Metaverse in education. To this end, this paper aims to provide a systematic literature review of Metaverse in education. This paper is a comprehensive survey of the Metaverse in education, with a focus on current technologies, challenges, opportunities, and future directions. First, we present a brief overview of the Metaverse in education, as well as the motivation behind its integration. Then, we survey some important characteristics for the Metaverse in education, including the personal teaching environment and the personal learning environment. Next, we envisage what variations of this combination will bring to education in the future and discuss their strengths and weaknesses. We also review the state-of-the-art case studies (including technical companies and educational institutions) for Metaverse in education. Finally, we point out several challenges and issues in this promising area.
Chenyuan Wu, B.R. Mehta, Mohammad Javad Amiri, Ryan Marcus · 5 authors
This paper presents AdaChain, a learning-based blockchain framework that adaptively chooses the best permissioned blockchain architecture in order to optimize effective throughput for dynamic transaction workloads. AdaChain addresses the challenge in the Blockchain-as-a-Service (BaaS) environments, where a large variety of possible smart contracts are deployed with different workload characteristics. AdaChain supports automatically adapting to an underlying, dynamically changing workload through the use of reinforcement learning. When a promising architecture is identified, AdaChain switches from the current architecture to the promising one at runtime in a way that respects correctness and security concerns. Experimentally, we show that AdaChain can converge quickly to optimal architectures under changing workloads, significantly outperform fixed architectures in terms of the number of successfully committed transactions, all while incurring low additional overhead.
Jiayi Sun, Wensheng Gan, Han-Chieh Chao, Philip S. Yu
As a fusion of various emerging digital technologies, the Metaverse aims to build a virtual shared digital space. It is closely related to extended reality, digital twin, blockchain, and other technologies. Its goal is to build a digital space based on the real world, form a virtual economic system, and expand the space of human activities, which injects new vitality into the social, economic, and other fields. In this article, we make the following contributions. We first introduce the basic concepts such as the development process, definition, and characteristics of the Metaverse. After that, we analyze the overall framework and supporting technologies of the Metaverse and summarize the status of common fields. Finally, we focus on the security and privacy issues that exist in the Metaverse, and give corresponding solutions or directions. We also discuss the challenges and possible research directions of the Metaverse. We believe this comprehensive review can provide an overview of the Metaverse and research directions for some multidisciplinary studies.
Blockchain systems essentially consist of two levels: The network level has the responsibility of distributing an ordered stream of transactions to all nodes of the network in exactly the same way, even in the presence of a certain amount of malicious parties (byzantine fault tolerance). On the node level, each node then receives this ordered stream of transactions and executes it within some sort of transaction processing system, typically to alter some kind of state. This clear separation into two levels as well as drastically different application requirements have led to the materialization of the network level in form of so-called blockchain frameworks. While providing all the "blockchain features", these frameworks leave the node level backend flexible or even left to be implemented depending on the specific needs of the application. In the following paper, we present how to integrate a highly versatile transaction processing system, namely a relational DBMS, into such a blockchain framework. As framework, we use the popular Tendermint Core, now part of the Ignite/Cosmos eco-system, which can run both public and permissioned networks and combine it with relational DBMSs as the backend. This results in a "relational blockchain", which is able to run deterministic SQL on a fully replicated relational database. Apart from presenting the integration and its pitfalls, we will carefully evaluate the performance implications of such combinations, in particular, the throughput and latency overhead caused by the blockchain layer on top of the DBMS. As a result, we give recommendations on how to run such a systems combination efficiently in practice.
The rise of open and permissionless blockchains has introduced novel platforms for applications based on distributed data storage. At the application and business levels, long-established query languages such as SQL provide interoperability that can be complemented by blockchain-based data storage today, enabling permissionless and verifiable data storage along with decentralized execution across tens of thousands of nodes. However, when accessing one or more blockchains, interoperability is not provided today, posing challenges such as inhomogeneous data access in addition to different features and trade-offs, e.g. in data and distribution, scalability, and security. Towards interoperability in data access among the increasing number of blockchain platforms, this paper introduces a cross-chain query language for data access across blockchains. Similar to SQL, the language abstracts from implementation based on a data model compatible with the largest open and permissionless blockchains (OPB) today. The language, data model, and processing architecture are demonstrated and evaluated with an implemented prototype, aiming to contribute to the discussion on blockchain interoperability among OPB.
Roberto Garcı́a, Ana Cediel, Mercè Teixidó, Rosa Gil
Recent initiatives related to the Metaverse focus on better visualization, like augmented or virtual reality, but also persistent digital objects. To guarantee real ownership of these digital objects, open systems based on public blockchains and Non-Fungible Tokens (NFTs) are emerging together with a nascent decentralized and open creator economy. To manage this emerging economy in a more organized way, and fight the so common NFT plagiarism, we propose CopyrightLY, a decentralized application for authorship and copyright management. It provides means to claim content authorship, including supporting evidence. Content and metadata are stored in decentralized storage and registered on the blockchain. A token is used to curate these claims, and potential complaints, by staking it on them. Staking is incentivized by the fact that the token is minted using a bonding curve. The tokenomics include the resolution of complaints and enabling the monetization of curated claims. Monetization is achieved through licensing NFTs with metadata enhanced by semantic technologies. Semantic data makes explicit the reuse conditions transferred with the token while keeping the connection to the underlying copyright claims to improve the trustability of the NFTs. Moreover, the semantic metadata is flexible enough to enable licensing not just in the real world. Licenses can refer to reuses in specific locations in a metaverse, thus facilitating the emergence of creative economies in them.
Rongxin Xu, Qiujun Lan, Shiva Raj Pokhrel, Gang Li
The Internet of Things (IoT) and Distributed ledger technology (DLT) have significantly changed our daily lives. Due to their distributed operational environment and naturally decentralized applications, the convergence of these two technologies indicates a more lavish arrangement for the future. This article develops a comprehensive survey to investigate and illustrate state-of-the-art DLT for various IoT use cases, from smart homes to autonomous vehicles and smart cities. We develop a novel framework for conducting a systematic and comprehensive review of DLT over IoT by extending the knowledge graph approach. With relevant insights from this review, we extract innovative and pragmatic techniques to DLT design that enable high-performance, sustainable, and highly scalable IoT systems. Our findings support designing an end-to-end IoT-native DLT architecture for the future that fully coordinates network-assisted functionalities.
Mohammad Hossein Tabatabaei, Roman Vitenberg, Narasimha Raghavan Veeraragavan
The explosive advent of the blockchain technology has led to hundreds of blockchain systems in the industry, thousands of academic papers published over the last few years, and an even larger number of new initiatives and projects. Despite the emerging consolidation efforts, the area remains highly turbulent without systematization, educational materials, or cross-system comparative analysis. In this paper, we provide a systematic and comprehensive study of four popular yet widely different blockchain systems: Bitcoin, Ethereum, Hyperledger Fabric, and IOTA. The study is presented as a cross-system comparison, which is organized by clearly identified aspects: definitions, roles of the participants, entities, and the characteristics and design of each of the commonly used layers in the cross-system blockchain architecture. Our exploration goes deeper compared to what is currently available in academic surveys and tutorials. For example, we provide the first extensive coverage of the storage layer in Ethereum and the most comprehensive explanation of the consensus protocol in IOTA. The exposition is due to the consolidation of fragmented information gathered from white and yellow papers, academic publications, blogs, developer documentation, communication with the developers, as well as additional analysis gleaned from the source code. We hope that this survey will help the readers gain in-depth understanding of the design principles behind blockchain systems and contribute towards systematization of the area.
Cong Yue, Tien Tuan Anh Dinh, Zhongle Xie, Meihui Zhang · 7 authors
Verifiable ledger databases protect data history against malicious tampering. Existing systems, such as blockchains and certificate transparency, are based on transparency logs --- a simple abstraction allowing users to verify that a log maintained by an untrusted server is append-only. They expose a simple key-value interface without transactions. Building a practical database from transparency logs, on the other hand, remains a challenge. In this paper, we explore the design space of verifiable ledger databases along three dimensions: abstraction, threat model, and performance. We survey existing systems and identify their two limitations, namely, the lack of transaction support and the inferior efficiency. We then present GlassDB, a distributed database system that addresses these limitations under a practical threat model. GlassDB inherits the verifiability of transparency logs, but supports transactions and offers high performance. It extends a ledgerlike key-value store with a data structure for efficient proofs, and adds a concurrency control mechanism for transactions. GlassDB batches independent operations from concurrent transactions when updating the core data structures. In addition, we design a new benchmark for evaluating verifiable ledger databases, by extending YCSB and TPC-C benchmarks. Using this benchmark, we compare GlassDB against four baselines: reimplemented versions of three verifiable databases, and a verifiable map backed by a transparency log. Experimental results demonstrate that GlassDB is an efficient, transactional, and verifiable ledger database system.
Jun-Teng Yang, Wen-Yuan Chen, Che-Hua Li, Scott C. -H. Huang · 5 authors
Recent research in Internet of things has been widely applied for industrial practices, fostering the exponential growth of data and connected devices. Henceforth, data-driven AI models would be accessed by different parties through certain data-sharing policies. However, most of the current training procedures rely on the centralized data-collection strategy and a single computational server. However, such a centralized scheme may lead to many issues. Customer data stored in a centralized database may be tampered with so the provenance and authenticity of data cannot be justified. Once the aforementioned security concerns occur, the credibility of the trained AI models would be questionable and even unfavorable outcomes might be produced at the test stage. Lately, blockchain and AI, the two core technologies in Industry 4.0 and Web 3.0, have been explored to facilitate the decentralized AI training strategy. To serve on this very purpose, we propose a new system architecture called APPFLChain, namely an integrated architecture of a Hyperledger Fabric-based blockchain and a federated-learning paradigm. Our proposed new system allows different parties to jointly train AI models and their customers or stakeholders are connected by a consortium blockchain-based network. Our new system can maintain a high degree of security and privacy as users do not need to share sensitive personal information to the server. For numerical evaluation, we simulate a real-world scenario to illustrate the whole operational process of APPFLChain. Simulation results show that taking advantage of the characteristics of consortium blockchain and federated learning, APPFLChain can demonstrate favorable properties including untamperability, traceability, privacy protection, and reliable decision-making.
Dumitrel Loghin, Tien Tuan Anh Dinh, Aung Maw, Chen Gang · 6 authors
While state-of-the-art permissioned blockchains can achieve thousands of transactions per second on commodity hardware with x86/64 architecture, their performance when running on different architectures is not clear. The goal of this work is to characterize the performance and cost of permissioned blockchains on different hardware systems, which is important as diverse application domains are adopting t. To this end, we conduct extensive cost and performance evaluation of two permissioned blockchains, namely Hyperledger Fabric and ConsenSys Quorum, on five different types of hardware covering both x86/64 and ARM architecture, as well as, both cloud and edge computing. The hardware nodes include servers with Intel Xeon CPU, servers with ARM-based Amazon Graviton CPU, and edge devices with ARM-based CPU. Our results reveal a diverse profile of the two blockchains across different settings, demonstrating the impact of hardware choices on the overall performance and cost. We find that Graviton servers outperform Xeon servers in many settings, due to their powerful CPU and high memory bandwidth. Edge devices with ARM architecture, on the other hand, exhibit low performance. When comparing the cloud with the edge, we show that the cost of the latter is much smaller in the long run if manpower cost is not considered.
Blockchain introduces decentralized trust in peer-to-peer networks, advancing security and democratizing systems. Yet, a unified definition for decentralization remains elusive. Our Systematization of Knowledge (SoK) seeks to bridge this gap, emphasizing quantification and methodological coherence. We've formulated a taxonomy defining blockchain decentralization across five facets: consensus, network, governance, wealth, and transaction. Despite the prevalent focus on consensus decentralization, our novel index, based on Shannon entropy, provides comprehensive insights. Moreover, we delve into alternative metrics like the Gini and Nakamoto Coefficients and the Herfindahl-Hirschman Index (HHI), supplemented by an open-source Python tool on GitHub. In terms of methodology, blockchain research has often bypassed stringent scientific methods. By employing descriptive, predictive, and causal methods, our study showcases the potential of structured research in blockchain. Descriptively, we observe a trend of converging decentralization levels over time. Examining DeFi platforms reveals exchange and lending applications as more decentralized than their payment and derivatives counterparts. Predictively, there's a notable correlation between Ether's returns and transaction decentralization in Ether-backed stablecoins. Causally, Ethereum's transition to the EIP-1559 transaction fee model has a profound impact on DeFi transaction decentralization. To conclude, our work outlines directions for blockchain research, emphasizing the delicate balance among decentralization facets, fostering long-term decentralization, and the ties between decentralization, security, privacy, and efficiency. We end by spotlighting challenges in grasping blockchain decentralization intricacies.
Kyle P. Michelson, Anjali Sridharan, Umut Can Çabuk, Ethan Reesor · 9 authors
The Accumulate Protocol ("Accumulate") is an identity-based, Delegated Proof of Stake (DPoS) blockchain designed to power the digital economy through interoperability with Layer-1 blockchains, integration with enterprise tech stacks, and interfacing with the World Wide Web. Accumulate bypasses the trilemma of security, scalability, and decentralization by implementing a chain-of-chains architecture in which digital identities with the ability to manage keys, tokens, data, and other identities are treated as their own independent blockchains. This architecture allows these identities, known as Accumulate Digital Identifiers (ADIs), to be processed and validated in parallel over the Accumulate network. Each ADI also possesses a hierarchical set of keys with different priority levels that allow users to manage their security over time and create complex signature authorization schemes that expand the utility of multi-signature transactions. A two token system provides predictable costs for enterprise users, while anchoring all transactions to Layer-1 blockchains provides enterprise-grade security to everyone.
Jelle Hellings, Suyash Gupta, Sajjad Rahnama, Mohammad Sadoghi
The introduction of Bitcoin fueled the development of blockchain-based resilient data management systems that are resilient against failures, enable federated data management, and can support data provenance. The key factor determining the performance of such resilient data management systems is the consensus protocol used by the system to replicate client transactions among all participants. Unfortunately, existing high-throughput consensus protocols are costly and impose significant latencies on transaction processing, which rules out their usage in responsive high-performance data management systems. In this work, we improve on this situation by introducing the Proof-of-Execution consensus protocol (PoE), a consensus protocol designed for high-performance low-latency resilient data management. PoE introduces speculative execution, which minimizes latencies by starting execution before consensus is reached, and PoE introduces proof-of-executions to guarantee successful execution to clients. Furthermore, PoE introduces a single-round check-commit protocol to reduce the overall communication costs of consensus. Hence, we believe that PoE is a promising step towards flexible general-purpose low-latency resilient data management systems.
Byzantine consensus is a critical component in many permissioned Blockchains and distributed ledgers. We propose a new paradigm for designing BFT protocols called DQBFT that addresses three major performance and scalability challenges that plague past protocols: (i) high communication costs to reach geo-distributed agreement, (ii) uneven resource utilization hampering performance, and (iii) performance degradation under varying node and network conditions and high-contention workloads. Specifically, DQBFT divides consensus into two parts: 1) durable command replication without a global order, and 2) consistent global ordering of commands across all replicas. DQBFT achieves this by decentralizing the heavy task of replicating commands while centralizing the ordering process. Under the new paradigm, we develop a new protocol, Destiny that uses a combination of three techniques to achieve high performance and scalability: using a trusted subsystem to decrease consensus's quorum size, using threshold signatures to attain linear communication costs, reducing client communication. Our evaluations on 300-replica geo-distributed deployment reveal that DQBFT protocols achieve significant performance gains over prior art: $\approx$3x better throughput and $\approx$50\% better latency.
While increasingly more application-specific blockchains, or ledgers, are being implemented and deployed, exchanging information between these ledgers remains an open problem. Existing cross-ledger protocols (XLPs) exhibit a variety of limitations such as scalability, liveness, efficiency, among others. This paper proposes a new XLP, namely XLPN-22, which introduces a global topology for the consortium of ledgers to achieve better efficiency and scalability of cross-ledger data exchanges. In this work, we prove the safety and liveness of XLPN-22 and analyze its theoretical complexity. We also implement XLPN-22 on SciChain ledgers and evaluate it on up to 128 nodes, 8 ledgers, and 16,000 transactions. Experimental results show that XLPN-22 outperforms two baseline protocols, namely VLDB-20 and PODC-18, by 18--50\% and 64--84\%, respectively.
Ryan Shivers, Mohammad Ashiqur Rahman, Md Jobair Hossain Faruk, Hossain Shahriar · 6 authors
Ride-hailing and ride-sharing applications have recently gained popularity as a convenient alternative to traditional modes of travel. Current research into autonomous vehicles is accelerating rapidly and will soon become a critical component of a ride-hailing platforms architecture. Implementing an autonomous vehicle ride-hailing platform proves a difficult challenge due to the centralized nature of traditional ride-hailing architectures. In a traditional ride-hailing environment the drivers operate their own personal vehicles so it follows that a fleet of autonomous vehicles would be required for a centralized ride-hailing platform to succeed. Decentralization of the ride-hailing platform would remove a roadblock along the way to an autonomous vehicle ride-hailing platform by allowing owners of autonomous vehicles to add their vehicles to a community-driven fleet when not in use. Blockchain technology is an attractive choice for this decentralized architecture due to its immutability and fault tolerance. This thesis proposes a framework for developing a decentralized ride-hailing architecture that is verifiably secure. This framework is implemented on the Hyperledger Fabric blockchain platform. The evaluation of the implementation is done by applying known security models, utilizing a static analysis tool, and performing a performance analysis under heavy network load.
Traditional data collection, storage and processing of Electronic Health Records (EHR) utilize centralized techniques that pose several risks of single point of failure and lean the systems to a number of internal and external data breaches that compromise their reliability and availability. Blockchain is an emerging distributed technology that can solve these issues due to its immutability and architectural nature that prevent records manipulation or alterations. In this paper, we discuss the progress and opportunities of remote patient monitoring using futuristic blockchain technologies and its two primary frameworks: Ethereum and Hyperledger Fabric. We also discuss the possible blockchain use cases in software engineering for systematic, disciplined, and quantifiable application development. The study extends by introducing a system architecture for EHR data management using Ethereum as a model. We discuss the challenges and limitations along with the initial evaluation results of the proposed system and draw future research directions in this promising area.