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--- | ||
title: Aggregate Programming | ||
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# The Challenge of Maintaining Distributed Systems | ||
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The **progressive increase** in the number of interconnected devices, leads to a **rise in the costs** associated with maintaining distributed systems. This creates **significant challenges** in implementing software services on a **global scale** using the traditional approach of individually programming each agent. This situation drives the search for solutions aimed at improving the **autonomy** of computing systems and **reducing their complexity**. | ||
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## Aggregate Programming as a Relevant Approach | ||
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In this context, **aggregate programming** emerges as a relevant approach. It is based on the **functional composition** of **reusable collective behavior blocks**, with the goal of efficiently achieving **complex** and **resilient behaviors** in **dynamic networks**. | ||
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### Key Properties of Aggregate Programming | ||
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- **Self-stabilization** | ||
- **Independence from density** | ||
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These properties are initially studied on **basic building blocks**, such as: | ||
- **Broadcasting** | ||
- **Distance estimation** | ||
- **Data aggregation** | ||
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These building blocks are then transferred and validated on more **complex systems** created through **functional composition**. | ||
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### Conceptual Roots in Field Calculus | ||
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Aggregate programming finds its **conceptual roots** in **Field Calculus**. | ||
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title: Field Calculus | ||
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title: What is Collektive | ||
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# What is the purpose of Collektive? | ||
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# What is the purpose of Collektive? | ||
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# What problems does Collektive solve? | ||
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# What are the advantages of using Collektive? |