A Glimpse of the Matrix (Extended Version): Scalability Issues of a New Message-Oriented Data Synchronization Middleware

Matrix is a new message-oriented data synchronization middleware, used as a federated platform for near real-time decentralized applications. It features a novel approach for inter-server communication based on synchronizing message history by using a replicated data structure. We measured the structure of public parts in the Matrix federation as a basis to analyze the middleware\u27s scalability. We confirm that users are currently cumulated on a single large server, but find more small servers than expected. We then analyze network load distribution in the measured structure and identify scalability issues of Matrix\u27 group communication mechanism in structurally diverse federations

Matrix Decomposition – Analysis of an Access Control Approach on Transaction-based DAGs without Finality

The Matrix message-oriented middleware (see https://matrix.org) is gaining momentum as a basis for a decentralized, secure messaging system as shown, for example, by its deployment within the French government and by the Mozilla foundation. Thus, understanding the corresponding access control approach is important. This paper provides an ab- straction and an analysis of the access control approach followed by Matrix. We show that Matrix can be seen as a form of Distributed Ledger Technology (DLT) based on Transaction-based Directed Acyclic Graphs (TDAGs). TDAGs connect individual transactions to form a DAG, instead of collecting transactions in blocks as in blockchains. These TDAGs only provide causal order, eventual consistency, and no finality. However, unlike conventional DLTs, Matrix does not aim for a strict system-wide consensus. Thus, there is also no guarantee for a strict consensus on access rights. By de- composition of the Matrix approach, we show that a sound decen- tralized access control can be implemented for TDAGs in general, and for Matrix in particular, despite those weak guarantees. In addition, we discovered security issues in popular implementations and emphasize the need for a formal verification of the employed conflict resolution mechanism

Analysis of the Matrix Event Graph Replicated Data Type

Matrix is a new kind of decentralized, topic-based publish-subscribe middleware for communication and data storage that is getting particularly popular as a basis for secure instant messaging. By comparison with traditional decentralized communication systems, Matrix replaces pure message passing with a replicated data structure. This data structure, which we extract and call the Matrix Event Graph (MEG), depicts the causal history of messages. We show that this MEG represents an interesting and important replicated data type for decentralized applications that are based on causal histories of publish-subscribe events: First, we prove that the MEG is a Conflict-Free Replicated Data Type for causal histories and, thus, provides Strong Eventual Consistency (SEC). With SEC being among the best known achievable trade-offs in the scope of the well-known CAP theorem, the MEG provides a powerful consistency guarantee while being available during network partition. Second, we discuss the implications of byzantine attackers on the data type’s properties. We note that the MEG, as it does not strive for consensus or strong consistency, can cope with $n>f$ environments with $n$ participants, of which $f$ are byzantine. Furthermore, we analyze scalability: Using Markov chains, we study the number of forward extremities of the MEG over time and observe an almost optimal evolution. We conjecture that this property is inherent to the underlying spatially inhomogeneous random walk. With the properties shown, a MEG represents a promising element in the set of data structures for decentralized applications, but with distinct trade-offs compared to traditional blockchains and distributed ledger technologies

Analysis of the Matrix Event Graph Replicated Data Type

Matrix is a new kind of decentralized, topic-based publish-subscribe middleware for communication and data storage that is getting particularly popular as a basis for secure instant messaging. By comparison with traditional decentralized communication systems, Matrix replaces pure message passing with a replicated data structure. This data structure, which we extract and call the Matrix Event Graph (MEG), depicts the causal history of messages. We show that this MEG represents an interesting and important replicated data type for decentralized applications that are based on causal histories of publish-subscribe events: First, we prove that the MEG is a Conflict-Free Replicated Data Type for causal histories and, thus, provides Strong Eventual Consistency (SEC). With SEC being among the best known achievable trade-offs in the scope of the well-known CAP theorem, the MEG provides a powerful consistency guarantee while being available during network partition. Second, we discuss the implications of byzantine attackers on the data type’s properties. We note that the MEG, as it does not strive for consensus or strong consistency, can cope with $n>f$ environments with $n$ participants, of which $f$ are byzantine. Furthermore, we analyze scalability: Using Markov chains, we study the number of forward extremities of the MEG over time and observe an almost optimal evolution. We conjecture that this property is inherent to the underlying spatially inhomogeneous random walk. With the properties shown, a MEG represents a promising element in the set of data structures for decentralized applications, but with distinct trade-offs compared to traditional blockchains and distributed ledger technologies

Analysis of the Matrix Event Graph Replicated Data Type

Matrix is a new kind of decentralized, topic-based publish-subscribe middleware for communication and data storage that is getting particularly popular as a basis for secure instant messaging. By comparison with traditional decentralized communication systems, Matrix replaces pure message passing with a replicated data structure. This data structure, which we extract and call the Matrix Event Graph (MEG), depicts the causal history of messages. We show that this MEG represents an interesting and important replicated data type for decentralized applications that are based on causal histories of publish-subscribe events: First, we prove that the MEG is a Conflict-Free Replicated Data Type for causal histories and, thus, provides Strong Eventual Consistency (SEC). With SEC being among the best known achievable trade-offs in the scope of the well-known CAP theorem, the MEG provides a powerful consistency guarantee while being available during network partition. Second, we discuss the implications of byzantine attackers on the data type’s properties. We note that the MEG, as it does not strive for consensus or strong consistency, can cope with $n>f$ environments with $n$ participants, of which $f$ are byzantine. Furthermore, we analyze scalability: Using Markov chains, we study the number of forward extremities of the MEG over time and observe an almost optimal evolution. We conjecture that this property is inherent to the underlying spatially inhomogeneous random walk. With the properties shown, a MEG represents a promising element in the set of data structures for decentralized applications, but with distinct trade-offs compared to traditional blockchains and distributed ledger technologies

A Pattern Language for Designing Application-Level Communication Protocols and the Improvement of Computer Science Education through Cloud Computing

Networking protocols have been developed throughout time following layered architectures such as the Open Systems Interconnection model and the Internet model. These protocols are grouped in the Internet protocol suite. Most developers do not deal with low-level protocols, instead they design application-level protocols on top of the low-level protocol. Although each application-level protocol is different, there is commonality among them and developers can apply lessons learned from one protocol to the design of new ones. Design patterns can help by gathering and sharing proven and reusable solution to common, reoccurring design problems. The Application-level Communication Protocols Design Patterns language captures this knowledge about application-level protocol design, so developers can create better, more fitting protocols base on these common and well proven solutions. Another aspect of contemporary development technics is the need of distribution of software artifacts. Most of the development companies have started using Cloud Computing services to overcome this need; either public or private clouds are widely used. Future developers need to manage this technology infrastructure, software, and platform as services. These two aspects, communication protocols design and cloud computing represent an opportunity to contribute to the software development community and to the software engineering education curriculum. The Application-level Communication Protocols Design Patterns language aims to help solve communication software design. The use of cloud computing in programming assignments targets on a positive influence on improving the Analysis to Reuse skills of students of computer science careers

3rd Many-core Applications Research Community (MARC) Symposium. (KIT Scientific Reports ; 7598)

This manuscript includes recent scientific work regarding the Intel Single Chip Cloud computer and describes approaches for novel approaches for programming and run-time organization