Creating a distributed system that can effectively perform a task and subsequently achieve consensus on the result is a multi-faceted challenge that involves considerations of network design, consensus algorithms, fault tolerance, and often, the specific requirements of the application itself. This process is vital in systems such as blockchain technologies, multi-agent systems, and various distributed database systems.

Key Components of a Distributed System

1. Nodes: Independent computers that work together in the distributed system.
2. Network: Connects nodes, enabling communication.
3. Consensus Algorithm: Mechanism to achieve agreement among distributed processes/nodes on a single data value.
4. Task Execution System: Mechanism for performing the tasks distributed among nodes.

Implementing a Distributed System: Step by Step

Step 1: Defining the Task to be Executed

First, clearly define the task that needs to be executed across the distributed system. This could range from computing a complex algorithm, storing data, or processing transactions.

Step 2: Setting Up Nodes

Each node in the system should be set up with the necessary software and hardware capabilities to perform its part of the task. This might include installing specific software, allocating sufficient computing power, and ensuring reliable internet connectivity.

Step 3: Designing the Network Structure

Nodes need to be interconnected in a way that optimizes the performance of the task while minimizing latency and maximizing reliability. Common structures include:

• Star Network: Central node to which all other nodes connect.
• Mesh Network: Each node connected to multiple other nodes.
• Ring Network: Each node connected to two other nodes forming a ring.

Step 4: Implementing a Consensus Algorithm

A key component of any distributed system is the consensus algorithm. Several well-known algorithms include:

• Raft: Useful for distributed systems like databases, where a leader is elected to manage replication log.
• Paxos: Solves consensus with a minimum of three-phase commit which ensures consistency.
• Proof of Work/Stake: Commonly used in blockchain networks.

For each consensus algorithm, the key is to determine how nodes will communicate and reconcile data to ensure that they all agree on the status of the task and its output.

Step 5: Task Distribution and Execution

Each node receives an instruction on the task to be performed. Tasks can be distributed based on different strategies:

• Random Allocation: Tasks are assigned randomly to nodes.
• Round-robin Allocation: Tasks are distributed in a cyclic fashion.
• Load-based Allocation: Tasks are distributed based on the current load on each node.

Step 6: Collecting and Aggregating Results

As nodes complete their assignments, results need to be aggregated. This can be part of the consensus process, where nodes communicate their results and verify each other's outcomes to decide on the final consensus.

Step 7: Handling Failures

The system must be resilient. Implementing fault tolerance techniques like replicating tasks across multiple nodes or employing recovery mechanisms is crucial in case a node fails.

Examples of Practical Applications

• Blockchain and Cryptocurrencies: Bitcoin uses a proof of work consensus to agree on the state of transactions across all nodes (miners).
• Distributed Databases: Cassandra uses a form of Paxos to ensure data consistency across multiple data center locations.
• Cloud Computing Services: Amazon's DynamoDB utilizes a modified version of Paxos for its architecture, which ensures availability and reliability.

Key Points Summary

In conclusion, building a distributed system with a consensus on task results involves careful planning, robust network design, selecting the appropriate consensus algorithm, and ensuring fault tolerance and reliability. Each component plays a pivotal role in the seamless operation and reliability of the system, ensuring that it performs effectively under varying conditions and scales appropriately as more nodes are added or tasks become more complex.