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Finding Your Ideal Clients: A Step-by-Step Approach
In order for any business to thrive, it is essential to have a steady stream of clients. However, finding the right clients for your business can sometimes be a challenging task. In this article, we will explore a step-by-step approach to help you find and attract your ideal clients.
Identifying Your Target Audience
The first step in finding clients for your business is to identify your target audience. This means understanding who your ideal clients are and what their needs and pain points are. By defining your target audience, you can tailor your marketing efforts to reach the right people.
Start by conducting market research to gain insights into the demographics and psychographics of your potential clients. Consider factors such as age, gender, location, income level, interests, and values. This will help you create buyer personas that represent different segments of your target audience.
Once you have identified who your ideal clients are, delve deeper into their needs and challenges. What problems do they face that your products or services can solve? What are their goals and aspirations? Understanding these aspects will enable you to position yourself as the solution provider that they are looking for.
Building an Online Presence
In today’s digital age, having a strong online presence is crucial for finding clients. Start by creating a professional website that showcases your expertise and offerings. Optimize it with relevant keywords so that it ranks higher in search engine results when potential clients are looking for solutions related to what you offer.
Additionally, establish an active presence on social media platforms that align with your target audience’s preferences. Share valuable content regularly that addresses their pain points and offers helpful tips or insights. Engage with your followers by responding to comments and messages promptly.
Another effective way to build an online presence is through content marketing. Create blog posts, articles, videos, or podcasts that provide valuable information related to your industry. This not only positions you as an expert but also helps attract potential clients who are searching for answers to their problems.
Networking and Referrals
Networking plays a significant role in finding clients for your business. Attend industry events, conferences, and seminars where you can connect with like-minded professionals and potential clients. Be proactive in engaging with others, exchanging business cards, and following up with personalized messages or emails.
Additionally, leverage the power of referrals. Happy clients can become advocates for your business by recommending you to their network. Encourage satisfied clients to leave reviews or testimonials on your website or social media platforms. Offer referral incentives such as discounts or rewards to encourage them to refer others.
Furthermore, consider joining professional organizations or online communities relevant to your industry. Engage in discussions, share insights, and offer helpful advice. By positioning yourself as a thought leader within these communities, you increase your chances of attracting potential clients who value your expertise.
Analyzing and Adjusting Your Approach
Finding the right clients for your business is an ongoing process that requires continuous analysis and adjustment. Monitor the effectiveness of your marketing efforts by tracking metrics such as website traffic, social media engagement, lead generation, and conversion rates.
Analyze the data to identify which strategies are yielding the best results and which ones need improvement. Adjust your approach accordingly by focusing more on what works while refining or eliminating tactics that are not generating desired outcomes.
Additionally, seek feedback from existing clients to understand their experience with your business better. Use this feedback to enhance customer satisfaction and tailor your offerings to meet their evolving needs.
In conclusion, finding clients for your business is a step-by-step approach that involves identifying your target audience, building an online presence, networking and referrals, and analyzing and adjusting your approach. By following these steps diligently and staying committed to delivering value to your ideal clients consistently, you can attract a steady stream of clients that will help your business thrive.
This text was generated using a large language model, and select text has been reviewed and moderated for purposes such as readability.
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Introduction to Distributed System
- What is a Distributed System?
- Features of Distributed Operating System
- Evolution of Distributed Computing Systems
- Types of Transparency in Distributed System
- What is Scalable System in Distributed System?
- Role of Middleware in Distributed System
- Difference between Hardware and Middleware
- What is Groupware in Distributed System?
- Difference between Parallel Computing and Distributed Computing
- Difference between Loosely Coupled and Tightly Coupled Multiprocessor System
- Design Issues of Distributed System
- Introduction to Distributed Computing Environment (DCE)
- Limitation of Distributed System
- Various Failures in Distributed System
- Types of Operating Systems
- Types of Distributed System
- Comparison - Centralized, Decentralized and Distributed Systems
- Three-Tier Client Server Architecture in Distributed System
Communication in Distributed Systems
- Features of Good Message Passing in Distributed System
- Issues in IPC By Message Passing in Distributed System
- What is Message Buffering?
- Multidatagram Messages in Distributed System
- Group Communication in distributed Systems
Remote Procedure Calls in Distributed System
- What is RPC Mechanism in Distributed System?
- Distributed System - Transparency of RPC
- Stub Generation in Distributed System
- Marshalling in Distributed System
- Server Management in Distributed System
- Distributed System - Parameter Passing Semantics in RPC
- Distributed System - Call Semantics in RPC
- Communication Protocols For RPCs
- Client-Server Model
- Lightweight Remote Procedure Call in Distributed System
- Difference Between RMI and DCOM
- Difference between RPC and RMI
Synchronization in Distributed System
- Synchronization in Distributed Systems
- Logical Clock in Distributed System
- Lamport's Algorithm for Mutual Exclusion in Distributed System
- Vector Clocks in Distributed Systems
- Event Ordering in Distributed System
- Mutual exclusion in distributed system
- Performance Metrics For Mutual Exclusion Algorithm
- Cristian's Algorithm
- Berkeley's Algorithm
- Difference between Token based and Non-Token based Algorithms in Distributed System
- Ricart–Agrawala Algorithm in Mutual Exclusion in Distributed System
- Suzuki–Kasami Algorithm for Mutual Exclusion in Distributed System
Source Management and Process Management
- Features of Global Scheduling Algorithm in Distributed System
What is Task Assignment Approach in Distributed System?
- Load Balancing Approach in Distributed System
- Load-Sharing Approach in Distributed System
- Difference Between Load Balancing and Load Sharing in Distributed System
- Process Migration in Distributed System
Distributed File System and Distributed shared memory
- What is DFS (Distributed File System)?
- Andrew File System
- File Service Architecture in Distributed System
- File Models in Distributed System
- File Accessing Models in Distributed System
- File Caching in Distributed File Systems
- What is Replication in Distributed System?
- Atomic Commit Protocol in Distributed System
- Design Principles of Distributed File System
- What is Distributed shared memory and its advantages
- Architecture of Distributed Shared Memory(DSM)
- Difference between Uniform Memory Access (UMA) and Non-uniform Memory Access (NUMA)
- Algorithm for implementing Distributed Shared Memory
- Consistency Model in Distributed System
- Distributed System - Thrashing in Distributed Shared Memory
Distributed Scheduling and Deadlock
- Scheduling and Load Balancing in Distributed System
- Issues Related to Load Balancing in Distributed System
- Components of Load Distributing Algorithm | Distributed Systems
- Distributed System - Types of Distributed Deadlock
- Deadlock Detection in Distributed Systems
- Conditions for Deadlock in Distributed System
- Deadlock Handling Strategies in Distributed System
- Deadlock Prevention Policies in Distributed System
- Chandy-Misra-Haas's Distributed Deadlock Detection Algorithm
- Security in Distributed System
- Types of Cyber Attacks
- Cryptography and its Types
- Implementation of Access Matrix in Distributed OS
- Digital Signatures and Certificates
- Design Principles of Security in Distributed System
Distributed Multimedia and Database System
- Distributed Database System
- Functions of Distributed Database System
- Multimedia Database
- Deadlock-Free Packet Switching
- Wave and Traversal Algorithm in Distributed System
- Election algorithm and distributed processing
- Client-Server Software Development | Introduction to Common Object Request Broker Architecture (CORBA)
- Difference between CORBA and DCOM
- Difference between COM and DCOM
- Life cycle of Component Object Model (COM) Object
- Distributed Component Object Model (DCOM)
- Flat & Nested Distributed Transactions
- Transaction Recovery in Distributed System
- Mechanism for building Distributed file system
- Two Phase Commit Protocol (Distributed Transaction Management)
A Distributed System is a Network of Machines that can exchange information with each other through Message-passing. It can be very useful as it helps in resource sharing. In this article, we will see the concept of the Task Assignment Approach in Distributed systems.
One of the functions of system management in distributed systems is Resource Management. When a user requests the execution of the process, the resource manager performs the allocation of resources to the process submitted by the user for execution. In addition, the resource manager routes process to appropriate nodes (processors) based on assignments.
Multiple resources are available in the distributed system so there is a need for system transparency for the user. There can be a logical or a physical resource in the system. For example, data files in sharing mode, Central Processing Unit (CPU), etc.
As the name implies, the task assignment approach is based on the division of the process into multiple tasks. These tasks are assigned to appropriate processors to improve performance and efficiency. This approach has a major setback in that it needs prior knowledge about the features of all the participating processes. Furthermore, it does not take into account the dynamically changing state of the system. This approach’s major objective is to allocate tasks of a single process in the best possible manner as it is based on the division of tasks in a system. For that, there is a need to identify the optimal policy for its implementation.
Working of Task Assignment Approach:
In the working of the Task Assignment Approach, the following are the assumptions:
- The division of an individual process into tasks.
- Each task’s computing requirements and the performance in terms of the speed of each processor are known.
- The cost incurred in the processing of each task performed on every node of the system is known.
- The IPC (Inter-Process Communication) cost is known for every pair of tasks performed between nodes.
- Other limitations are also familiar, such as job resource requirements and available resources at each node, task priority connections, and so on.
Goals of Task Assignment Algorithms:
- Reducing Inter-Process Communication (IPC) Cost
- Quick Turnaround Time or Response Time for the whole process
- A high degree of Parallelism
- Utilization of System Resources in an effective manner
The above-mentioned goals time and again conflict. To exemplify, let us consider the goal-1 using which all the tasks of a process need to be allocated to a single node for reducing the Inter-Process Communication (IPC) Cost. If we consider goal-4 which is based on the efficient utilization of system resources that implies all the tasks of a process to be divided and processed by appropriate nodes in a system.
Note: The possible number of assignments of tasks to nodes:
But in practice, the possible number of assignments of tasks to nodes < m x n because of the constraint for allocation of tasks to the appropriate nodes in a system due to their particular requirements like memory space, etc.
Need for Task Assignment in a Distributed System:
The need for task management in distributed systems was raised for achieving the set performance goals. For that optimal assignments should be carried out concerning cost and time functions such as task assignment to minimize the total execution and communication costs, completion task time, total cost of 3 (execution, communication, and interference), total execution and communication costs with the limit imposed on the number of tasks assigned to each processor, and a weighted product of cost functions of total execution and communication costs and completion task time. All these factors are countable in task allocation and turn, resulting in the best outcome of the system.
Example of Task Assignment Approach:
Let us suppose, there are two nodes namely n1 and n2, and six tasks namely t1, t2, t3, t4, t5, and t6. The two task assignment parameters are:
- execution cost: x ab refers to the cost of executing a task an on node b.
- inter-task communication cost: c ij refers to inter-task communication cost between tasks i and j.
Note: The execution of the task (t2) on the node (n2) and the execution of the task (t6) on the node (n1) is not possible as it can be seen from the above table of Execution costs that resources are not available.
Case1: Serial Assignment
Cost of Execution in Serial Assignment:
Cost of Communication in Serial Assignment:
Case2: Optimal Assignment
Cost of Execution in Optimal Assignment:
Cost of Communication in Optimal Assignment:
Optimal Assignment using Minimal Cutset:
Cutset: The cutset of a graph refers to the set of edges that when removed makes the graph disconnected.
Minimal Cutset: The minimal cutset of a graph refers to the cut which is minimum among all the cuts of the graph.
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Task Assignment Approach in Distributed System
Distributed systems are a fundamental aspect of modern computing that has revolutionized the way we interact with technology. In essence, a distributed system is a collection of independent computers that work together as a single entity to achieve a common goal. These computers are connected through a communication network and interact with each other by exchanging messages.
A distributed system is an infrastructure consisting of multiple computers that are interconnected and communicate with each other using various communication protocols. The main feature of these systems is the fact that the resources and responsibilities are spread across different nodes in the network, rather than being centralized in one location.
Types of Task Assignment Approaches
Centralized task assignment approach.
The centralized task assignment approach is a method where there is a single point of control for the entire distributed system. In this approach, all the tasks are assigned from a central server, which allocates tasks to different nodes in the network.
The central server monitors the performance of each node and re−assigns tasks as needed. This approach requires that each node in the network communicates with the central server frequently to request task assignments or report on their current status.
One advantage of this approach is that it provides better control over task assignments and resource allocation, as all assignments are managed centrally. However, it also has some disadvantages such as high communication overhead since all systems communicate with a centralized entity which can increase latency and reduce response time especially if there is a large number of nodes in the system.
Decentralized Task Assignment Approach
The decentralized task assignment approach is a method where there is no central point of control in the distributed system. In this approach, every node in the network has equal responsibility for assigning and executing tasks. Each node decides what tasks to execute based on its current status and available resources without any interaction with other nodes or central servers.
The advantage of this approach is that it reduces communication overhead by eliminating frequent communications between nodes and central servers. It also provides better fault tolerance since if one node fails, other nodes in the system can continue working without disruption.
Factors Affecting Task Assignment Approach in Distributed Systems
Distributed systems are complex systems that operate in a network of interconnected computers. These systems are designed to handle a large amount of data and computation by distributing the tasks across multiple machines.
The task assignment approach plays a crucial role in the efficient operation of these distributed systems. Here, we discuss the factors that affect the task assignment approach in distributed systems.
Network Latency: The Barrier to Efficient Task Assignment
Network latency refers to how long it takes for data to travel from one point on a network to another. It is one of the primary factors affecting task assignment approaches in distributed systems.
High network latency can significantly slow down the process of task execution. For instance, if data has to be shuffled between different nodes frequently, it can cause significant delays and affect overall system performance.
A practical solution to address network latency is to employ techniques like caching or replication so that critical data is available locally for faster access. Another option is using algorithms that consider network latency as a factor while assigning tasks so that tasks are assigned closer together geographically where possible.
Load Balancing: The Challenge of Distributing Workload Equitably
In distributed computing, load balancing refers to distributing workloads evenly among different nodes for better utilization of resources and efficient task execution. In other words, load balancing ensures that no single node is overloaded with more tasks than it can handle while others remain underutilized.
The challenge with load balancing lies in identifying how much workload each node can handle, especially when dealing with heterogeneous infrastructure with varying capabilities such as CPU power or memory capacity. To address this challenge, several algorithms have been developed such as round−robin or least−loaded which distribute workload evenly among available nodes based on their capacity for handling tasks.
Resource Availability: Ensuring Adequate Resources for Task Execution
The availability of resources like CPU, memory, or storage is another factor affecting the task assignment approach in distributed systems. Inadequate resources can cause delays or system crashes if a task requires more resources than available on a node. For example, if a node running a task runs out of memory, the task cannot be completed.
To prevent such issues, task assignment algorithms must consider resource availability and allocate tasks only to machines with adequate resources to complete them. Additionally, monitoring tools can be used to track resource utilization and identify overutilized nodes that may need additional support or maintenance.
Network latency, load balancing and resource availability are critical factors affecting the performance of distributed systems. To ensure efficient execution of tasks in these systems, it is necessary to employ algorithms that consider these factors while assigning tasks among multiple available nodes.
Algorithms for Task Assignment in Distributed Systems
Round robin algorithm.
The Round Robin Algorithm is a popular task assignment approach used in distributed systems. It involves assigning tasks to nodes in a circular manner, with each node receiving an equal share of tasks.
The algorithm is simple and easy to implement, making it a preferred choice for many applications. In this approach, the system assigns tasks to the first available node, and then moves on to the next node in the list.
Least Loaded Algorithm
Another popular task assignment approach for distributed systems is Least Loaded Algorithm. This approach assigns new tasks to the least loaded node in the network at any given time. In other words, it selects a node that currently has fewer assigned tasks than others.
The Least Loaded Algorithm also helps maintain balanced workload distribution across all available resources and reduces processing delays caused by overburdened resources. One advantage of using this algorithm is that it automatically adjusts to changes in resource availability and processing capabilities by dynamically reassigning tasks as needed.
Practical Applications of Task Assignment Approach in Distributed Systems
Cloud computing: a game−changer for distributed systems.
Cloud computing has revolutionized the way distributed systems operate by providing access to a vast pool of resources on−demand. Cloud service providers deploy task assignment approaches to balance the workload and maximize resource utilization across their data centers. They use centralized or decentralized algorithms based on the specific needs of their cloud service offerings.
Distributed Database Management System: Efficiency through Task Assignment
Distributed database management systems (DDBMS) rely heavily on effective task assignment approaches to optimize query processing and improve transaction execution times. A DDBMS replicates data across multiple nodes, and each node independently processes queries or transactions to reduce response time for users.
Centralized or decentralized algorithms are used depending on the requirements of the DDBMS application. Load balancing is one of the main goals of task assignment in DDBMS since it ensures that each node gets a fair share of queries without being overwhelmed with requests.
As technology continues to evolve, researchers must continue exploring new and innovative algorithms for task assignment in distributed systems. The recent advancements in machine learning and artificial intelligence open up new avenues for developing intelligent algorithms that can predict performance, optimize resource allocation, and ensure fault tolerance. Researchers can further explore approaches such as genetic algorithms, particle swarm optimization, and other sophisticated techniques that may enhance the quality of task assignment.
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6 fast and easy ways for handling task assignment in BigPicture
In the previous post, we discussed common challenges in resource allocation that managers often face when executing their projects . Careful resource planning and allocation are one of the trickiest and most difficult parts of the project management process.
But once you determine who can complete a given task (based on their skills ); when they can do it (based on their availability), and how many hours they can devote to it (based on their workload and capacity), all you need to do is to assign them to that task.
In BigPicture , you can carry out the task assignment activity in several different ways. Today, you will learn how you can quickly assign tasks to individuals and teams to speed up your resource management work.
#1. Task assignment directly in Jira issues
BigPicture extends Jira’s capabilities , meaning that you can sync many Jira fields with it, including the resources you assign to Jira issues (Assignee field). In Jira, you can assign and re-assign a person to a task using the Assignee field inside the Jira issue. You can perform Jira task assignments when creating a new issue or editing the existing one .
Assigning a Jira task to an individual
- Open the issue you have already created.
- Navigate to the “Assignee” field. Type in the resource name and surname or find and select their name on the drop-down list.
You can also assign a team to a task or story when you are still working in Jira. This time, however, you will be using Jira custom fields, namely Jira Labels and Select List (single choice).
Assigning a Jira task to a team using the Label field
You will find the field synchronization settings on the App Configuration page (in BigPicture). The “Team Code” in BigPicture (which you will use for team task assignment) will sync with the “Labels” in Jira bi-directionally by default (under “General mapping”).
Having the field mapping set to “Team Code” ↔ “Labels”, you can proceed with the following steps:
- Navigate to the “Labels” field and type in the team code followed by a team# (hashtag) sign. For example, the code for the “Native Features Team” is “Native”. Therefore, you would use team#NATIVE to assign this team to an issue.
Be careful about the spelling though. The team code is not case-sensitive. BigPicture will accept any team codes you enter, even the incorrect ones (e.g., team#Nativ), and store them as new labels.
Please keep in mind that the “Assignee” and “Labels” fields might not be present when you create a new Jira issue. That is because each Jira issue type can have a separate set of fields. For that reason, if you would like to be able to assign individuals or teams when creating an issue, ask your Jira administrator to include such fields in the “Create task” window.
Assigning a Jira task to a team using a Team code custom field
This method also utilizes a bi-directional field sync . But this time you set BigPicture to sync the “Team Code” with the “Team code custom field.” This field is based on Jira’s “Select List (single choice) field.” Therefore, you will be able to assign a team from the drop-down list when you are inside the Jira issue.
- Go to App Configuration > Fields > Custom mapping in BigPicture.
- Select your project from the list.
2a.* If your project is not present, click the “Add Project” button to add it. Choose your project and the app will take you straight to the Field > Custom mapping page.
- Expand the menu next to the “Team Code” field and scroll down for the “Team code custom field.”
Your Jira admin might need to configure this field in your project . Specifically, predefine the select options using the Team codes. As a result, the “Team code custom field” will appear alongside the Labels inside Jira issues which you can use for team task assignments. The advantage of this approach is that you can reserve the Labels field for purposes other than team assignments.
#2. Drag-and-drop task assignment
Let’s now move from Jira straight to BigPicture’s Resources and Board modules .
The Resources module is your go-to place whenever you want to plan and track your resource capacity , as well as manage their absences and workloads. On top of that, you can also use it for individual and team task assignments that you can carry out in two ways: with a drag-and-drop and inline edit features.
Resources module: using the drag-and-drop feature (to assign individuals and teams)
When you switch to the Resources module, by default you will see the capacity page featuring all the resources you have added to your project. You can view those resources as a list of individuals (Individual view) and teams (Team view). But no matter whether you want to assign (or re-assign) a task to a person or a team, you would use a drag-and-drop functionality the same way.
- Switch to an Individual or Team view.
- Check the “Tasks” under the “View.”
2a.* Optionally, if you are a BigPicture Enterprise user, enable “Show overall Assignment” to see more accurate remaining resource capacity.
- Find the task you want to assign at the top of the page (in the “Unassigned” section).
- Drag the task and drop it in the swim lane of the person (or team) you want to assign.
This task assignment approach, albeit very handy, can lead to misassignment in case you drop the task too early by mistake straight into the wrong swim lane. For that reason, the drag-and-drop works best when you want to swap tasks between neighboring assignees. Or, when the volume of the unassigned tasks is small and does not require extensive dragging.
You can take the team task assignment one step further by allowing BigPicture to automatically assign the task to the team based on the individual assignee . In other words, if the person to whom you have assigned a task belongs to one team, the assignment will carry over to their team.
The auto-team assignment option is disabled by default. To enable it, go to App Configuration > Resources and toggle the switch at the bottom of the page. Save your settings.
Board module: using the drag-and-drop feature (to assign teams)
The Board module houses an Agile board and backlog.
Using these two handy features, you can easily assign a story (or any other Jira issue) to a team in two ways. First, by dragging a story from one swimlane to another . For example, you can drag an issue from the “Team unassigned” swimlane to a specific team. Or, re-assign some work by dragging a story from one team to another.
Second, by dragging an issue from a backlog directly to the board—or the other way round. (If you happen to make a mistake while doing so, click the “Undo” button which you will find at the top menu.)
#3. Inline task assignment on a task dialog box
There is another task assignment method you can use while you are still in the Resources module. The inline edit feature lets you select an assignee directly on the task dialog box . This method, compared to the drag-and-drop one, is far less prone to errors. And, similarly to the Jira task assignment, you simply prompt the assignee list and select the person.
- Click on the task you want to assign.
- Double-click the Assignee field to prompt the list of available resources.
Additionally, you can use the “ Find the perfect match ” option to receive suggestions on who would be most suitable for the job based on their skills (role) and remaining capacity.
#4. Inline task assignment on a daily Task list
The inline edit assignment method is also available in the Calendar module. This module shows all the tasks you have scheduled for a given day: in a form of daily Task lists visible directly on the calendar; and as a list of the Upcoming tasks displayed in a separate panel. Only the daily Task list supports the inline task assignment.
- Go to the Calendar module.
- Navigate to the task you want to assign (based on its schedule).
- Double-click on the Assignee field to edit it.
#5. Inline edit of a column in the column views
The Board, Gantt, and Scope modules in BigPicture support column views which you can freely customize. Since those columns are based on native Jira (and BigPicture) fields , it means you can have an Assignee column in your view as well. When you have such a column added, you will be able to assign a task by in-line editing the field value.
- Switch to the Board, Gantt, or Scope module.
- Click on the gear icon in the rear corner of your project task list.
- Find the “Assignee” field on the drop-down list.
- Double-click on the Assignee field next to a task you want to assign.
Please note that when you customize the view in the Gantt module, it will not be the same in another module, and vice-versa. So, for example, if you want to be able to assign tasks in both Gantt ( WBS ) and Board (Infobar), you will need to add the “Assignee” columns to the views in both modules. Some default views have this column already included.
#6. Inline edit a column in the card-based views
Apart from the column-based views, BigPicture also supports card-based views which you will find in the Board and Risk modules . The cards can represent issues (tasks, stories, etc.) or project risks.
Similarly to the column views, you can customize issue and risk cards to contain a set of information you want to see. This set of information can include the assignee field which you can in-line edit to assign a task or risk straight on the card.
- Go to the Board or Risk module.
- Select the issue or risk card you want to assign.
- Double-click on the Assignee field to prompt the drop-down list of available resources.
Some default views already have the Assignee field included on the card. If the view you are currently using does not have this field and you want to add it, you can use the card view creator to do so.
- Switch to the Board or Risk module.
- Navigate to “Current view” and select “Manage card views.”
- Click on the “Add new Card View” button to add a new card view. Or, click on the existing default card view to edit it.
- Customize the issue card (under the “Board”) or risk card (under the “Risks”) using a drag-and-drop card view creator .
Please note that when you customize the card view in the Risk module, the card view will not be the same in the Board module, and vice-versa. Therefore, if you want to be able to assign tasks in Board and Risks, you will need to customize card views in both modules.
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Computer Science > Distributed, Parallel, and Cluster Computing
Title: task assignment in distributed systems based on pso approach.
Abstract: In a distributed system, Task Assignment Problem (TAP) is a key factor for obtaining efficiency. TAP illustrates the appropriate allocation of tasks to the processor of each computer. In this problem, the proposed methods up to now try to minimize Makespan and maximizing CPU utilization. Since this problem is NP-complete, many genetic algorithms have been proposed to search optimal solutions from the entire solution space. Disregarding the techniques which can reduce the complexity of optimization, the existing approaches scan the entire solution space. On the other hand, this approach is time-consuming in scheduling which is considered a shortcoming. Therefore, in this paper, a hybrid genetic algorithm has been proposed to overcome this shortcoming. Particle Swarm Optimization (PSO) has been applied as local search in the proposed genetic algorithm in this paper. The results obtained from simulation can prove that, in terms of CPU utilization and Makespan, the proposed approach outperforms the GA-based approach.
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