Starvation in DBMS is a problem that happens when some processes are unable to get the resources they need because other processes keep getting priority. This can happen in situations like locking or scheduling, where some processes keep getting the resources first, leaving others waiting indefinitely.
This can cause delays or even stop certain operations from completing. In this article, we will explore what causes starvation, its effects, and how it can be prevented to make sure all processes are treated fairly.
StarvationExample 1:
Imagine you are waiting at a restaurant to place your order. Every time the waiter comes, they serve people who arrived after you because they are VIPs or because the waiter is prioritizing large group orders. You’ve been waiting for hours, but your turn never comes. This is similar to starvation, where someone is stuck waiting indefinitely while others get served first.
Example 2:
Suppose there are 3 transactions namely T1, T2, and T3 in a database that is trying to acquire a lock on data item ' I '. Now, suppose the scheduler grants the lock to T1(maybe due to some priority), and the other two transactions are waiting for the lock. As soon as the execution of T1 is over, another transaction T4 also comes over and requests a lock on data item I. Now, this time the scheduler grants lock to T4, and T2, T3 has to wait again. In this way, if new transactions keep on requesting the lock, T2 and T3 may have to wait for an indefinite period of time, which leads to Starvation.
Reasons for Starvation
Starvation in DBMS happens when some transactions or processes are unable to get the resources they need, often because other processes are prioritized or due to poor resource management. Here are the main reasons for starvation in simple terms:
- Unfair Prioritization: If lower-priority processes keep competing with higher-priority ones, they might be ignored for a long time, leading to indefinite waiting.
- Inappropriate Locking Strategy: When resources are managed poorly, such as using a priority queue, lower-priority processes may never get access to locked resources.
- Uncontrolled Resource Allocation: If processes keep passing resources to others without considering the system’s overall needs, some processes might never get the resources they require.
- Queue Mismanagement: If resources are always passed to the next process in a queue, new processes keep getting added, and some may end up waiting indefinitely.
- Repeated Victim Selection: Sometimes, the same transaction is repeatedly chosen as a "victim" during resource allocation, causing it to stay stuck without progress.
- Resource Leakage: If resources are lost or mismanaged due to system errors, there may not be enough available to meet the demands of all processes.
- High Demand vs. Limited Resources: If the demand for resources is much higher than the supply, no matter how well resources are managed, some processes will inevitably experience starvation.
- Random Resource Allocation: If resources are assigned randomly instead of following a proper queue, some processes may end up waiting much longer than others.
- Denial-of-Service Attacks: Intentional attacks can overwhelm the system, making it impossible for legitimate processes to get the resources they need, causing starvation.
Solutions to starvation
- Increase Priority Over Time: If a process or transaction has been waiting too long, its priority can be gradually increased. This ensures it will eventually be served. However, care should be taken as newer processes may end up waiting longer.
- Modification in Victim Selection algorithm: If a transaction has been a victim of repeated selections, then the algorithm can be modified by lowering its priority over other transactions.
- First Come First Serve approach: A fair scheduling approach i.e. FCFS can be adopted, In which the transaction can acquire a lock on an item in the order, in which the requested lock.
- Wait-die and wound wait scheme: These techniques use timestamps to decide the order of resource allocation, ensuring older transactions are prioritized, which helps prevent starvation.
- Timeout Mechanism: A timeout mechanism can be implemented in which a transaction is only allowed to wait for a certain amount of time before it is aborted or restarted. This ensures that no transaction waits indefinitely, and prevents the possibility of starvation.
- Resource Reservation: A resource reservation scheme can be used to allocate resources to a transaction before it starts execution. This ensures that the transaction has access to the necessary resources and reduces the chances of waiting for a resource indefinitely.
- Preemption: Preemption involves the forcible removal of a lock from a transaction that has been waiting for a long time, in favor of another transaction that has a higher priority or has been waiting for a shorter time. Preemption ensures that no transaction waits indefinitely, and prevents the possibility of starvation.
- Dynamic Lock Allocation: In this approach, locks are allocated dynamically based on the current state of the system. The system may analyze the current lock requests and allocate locks in such a way that prevents deadlocks and reduces the chances of starvation.
- Parallelism: By allowing multiple transactions to execute in parallel, the system can ensure that no transaction waits indefinitely, and reduces the chances of starvation. This approach requires careful consideration of the potential for conflicts and race conditions between transactions.
Techniques Used by DBMSs to Prevent or Mitigate Starvation
Starvation in a DBMS can harm system performance and fairness. To solve this problem, different methods are used to make sure resources are shared properly and all processes or transactions get a fair chance. Here’s a closer look at these solutions:
Resource Allocation Policies
Purpose: Ensures resources are distributed fairly among transactions and processes.
How It Works:
- DBMSs implement policies to allocate resources based on predefined fairness rules.
- These policies prevent specific transactions or processes from being perpetually denied access to resources.
- For example, round-robin or proportional sharing techniques can ensure balanced allocation.
Benefits:
- No process or transaction consistently gets priority over others.
- Promotes equitable sharing of resources, reducing the risk of starvation.
Priority-Based Scheduling
Purpose: Ensures high-priority tasks are executed first while considering fairness for lower-priority ones.
How It Works:
- DBMSs assign priorities to transactions or processes based on factors like urgency, importance, or wait time.
- High-priority processes are given preference, but long-waiting low-priority processes can have their priority dynamically increased to prevent starvation.
- Techniques like aging (gradually increasing the priority of waiting tasks) are used.
Benefits:
- Balances immediate needs (high-priority tasks) with fairness (preventing indefinite delays for low-priority tasks).
Read more about Priority-Based Scheduling, Here.
Timeout Mechanisms
Purpose: Prevents processes or transactions from being blocked indefinitely.
How It Works:
- A timeout period is set for resource requests.
- If a transaction waits longer than the timeout period, the resources it holds are released, or the process is restarted with a fresh attempt.
- This prevents deadlocks and prolonged blocking of other processes.
Benefits:
- Frees up resources for other waiting transactions.
- Ensures no process is stuck indefinitely, reducing the likelihood of starvation.
Resource Management Techniques
Purpose: Prevents any single transaction or process from monopolizing resources.
How It Works:
- Resource Quotas: Each transaction is allocated a specific amount of resources. Once it reaches the quota, it must release resources before continuing.
- Resource Limits: Caps are placed on the number of resources any transaction can hold, ensuring availability for others.
- Dynamic reallocation of unused resources ensures fair distribution.
Benefits:
- Limits excessive resource usage by individual transactions.
- Promotes balanced and efficient resource utilization.
These techniques collectively help DBMSs ensure fairness, prevent indefinite waiting, and maintain overall system efficiency, even under high demand or conflicting priorities.
Disadvantages of Starvation
- Decreased performance: Starvation can cause decreased performance in a DBMS by preventing transactions from making progress and causing a bottleneck.
- Increased response time: Starvation can increase response time for transactions that are waiting for resources, leading to poor user experience and decreased productivity.
- Inconsistent data: If a transaction is unable to complete due to starvation, it may leave the database in an inconsistent state, which can lead to data corruption and other problems.
- Difficulty in troubleshooting: Starvation can be difficult to troubleshoot because it may not be immediately apparent which transaction is causing the problem.
- Potential for deadlock: If multiple transactions are competing for the same resources, starvation can lead to deadlock, where none of the transactions can proceed, causing a complete system failure.
Conclusion
Starvation in DBMS is a serious issue that can affect the fairness, efficiency, and overall performance of a database system. It occurs when certain processes or transactions are unable to get the resources they need due to unfair prioritization or poor resource management. This can lead to delays, increased response times, and even system failure.
However, by implementing effective solutions like fair scheduling, timeout mechanisms, and better resource management techniques, starvation can be minimized or prevented altogether. Ensuring all transactions and processes are treated fairly not only improves the performance of the DBMS but also creates a more reliable and efficient system. Addressing starvation is essential for maintaining consistency, ensuring smooth operation, and providing a positive user experience in database systems.
Similar Reads
DBMS Tutorial â Learn Database Management System Database Management System (DBMS) is a software used to manage data from a database. A database is a structured collection of data that is stored in an electronic device. The data can be text, video, image or any other format.A relational database stores data in the form of tables and a NoSQL databa
7 min read
Basic of DBMS
Introduction of DBMS (Database Management System)A Database Management System (DBMS) is a software solution designed to efficiently manage, organize, and retrieve data in a structured manner. It serves as a critical component in modern computing, enabling organizations to store, manipulate, and secure their data effectively. From small application
8 min read
History of DBMSThe first database management systems (DBMS) were created to handle complex data for businesses in the 1960s. These systems included Charles Bachman's Integrated Data Store (IDS) and IBM's Information Management System (IMS). Databases were first organized into tree-like structures using hierarchica
7 min read
DBMS Architecture 1-level, 2-Level, 3-LevelA database stores important information that needs to be accessed quickly and securely. Choosing the right DBMS architecture is essential for organizing, managing, and maintaining the data efficiently. It defines how users interact with the database to read, write, or update information. The schema
7 min read
Difference between File System and DBMSA file system and a DBMS are two kinds of data management systems that are used in different capacities and possess different characteristics. A File System is a way of organizing files into groups and folders and then storing them in a storage device. It provides the media that stores data as well
6 min read
Entity Relationship Model
Introduction of ER ModelThe Entity-Relationship Model (ER Model) is a conceptual model for designing a databases. This model represents the logical structure of a database, including entities, their attributes and relationships between them. Entity: An objects that is stored as data such as Student, Course or Company.Attri
10 min read
Structural Constraints of Relationships in ER ModelStructural constraints, within the context of Entity-Relationship (ER) modeling, specify and determine how the entities take part in the relationships and this gives an outline of how the interactions between the entities can be designed in a database. Two primary types of constraints are cardinalit
5 min read
Generalization, Specialization and Aggregation in ER ModelUsing the ER model for bigger data creates a lot of complexity while designing a database model, So in order to minimize the complexity Generalization, Specialization, and Aggregation were introduced in the ER model. These were used for data abstraction. In which an abstraction mechanism is used to
4 min read
Introduction of Relational Model and Codd Rules in DBMSThe Relational Model is a fundamental concept in Database Management Systems (DBMS) that organizes data into tables, also known as relations. This model simplifies data storage, retrieval, and management by using rows and columns. Coddâs Rules, introduced by Dr. Edgar F. Codd, define the principles
14 min read
Types of Keys in Relational Model (Candidate, Super, Primary, Alternate and Foreign)In the context of a relational database, Keys are one of the basic requirements of a relational database model. keys are fundamental components that ensure data integrity, uniqueness, and efficient access. It is widely used to identify the tuples(rows) uniquely in the table. We also use keys to set
8 min read
Mapping from ER Model to Relational ModelConverting an Entity-Relationship (ER) diagram to a Relational Model is a crucial step in database design. The ER model represents the conceptual structure of a database, while the Relational Model is a physical representation that can be directly implemented using a Relational Database Management S
7 min read
Strategies for Schema design in DBMSThere are various strategies that are considered while designing a schema. Most of these strategies follow an incremental approach that is, they must start with some schema constructs derived from the requirements and then they incrementally modify, refine, or build on them. In this article, let's d
7 min read
Relational Model
Introduction of Relational Algebra in DBMSRelational Algebra is a formal language used to query and manipulate relational databases, consisting of a set of operations like selection, projection, union, and join. It provides a mathematical framework for querying databases, ensuring efficient data retrieval and manipulation. Relational algebr
9 min read
SQL Joins (Inner, Left, Right and Full Join)SQL joins are fundamental tools for combining data from multiple tables in relational databases. Joins allow efficient data retrieval, which is essential for generating meaningful observations and solving complex business queries. Understanding SQL join types, such as INNER JOIN, LEFT JOIN, RIGHT JO
5 min read
Join operation Vs Nested query in DBMSThe growth of technology and automation coupled with exponential amounts of data has led to the importance and omnipresence of databases which, simply put, are organized collections of data. Considering a naive approach, one can theoretically keep all the data in one large table, however that increa
5 min read
Tuple Relational Calculus (TRC) in DBMSTuple Relational Calculus (TRC) is a non-procedural query language used in relational database management systems (RDBMS) to retrieve data from tables. TRC is based on the concept of tuples, which are ordered sets of attribute values that represent a single row or record in a database table. TRC is
4 min read
Domain Relational Calculus in DBMSDomain Relational Calculus is a non-procedural query language equivalent in power to Tuple Relational Calculus. Domain Relational Calculus provides only the description of the query but it does not provide the methods to solve it. In Domain Relational Calculus, a query is expressed as, { < x1, x2
2 min read
Relational Algebra
Introduction of Relational Algebra in DBMSRelational Algebra is a formal language used to query and manipulate relational databases, consisting of a set of operations like selection, projection, union, and join. It provides a mathematical framework for querying databases, ensuring efficient data retrieval and manipulation. Relational algebr
9 min read
SQL Joins (Inner, Left, Right and Full Join)SQL joins are fundamental tools for combining data from multiple tables in relational databases. Joins allow efficient data retrieval, which is essential for generating meaningful observations and solving complex business queries. Understanding SQL join types, such as INNER JOIN, LEFT JOIN, RIGHT JO
5 min read
Join operation Vs Nested query in DBMSThe growth of technology and automation coupled with exponential amounts of data has led to the importance and omnipresence of databases which, simply put, are organized collections of data. Considering a naive approach, one can theoretically keep all the data in one large table, however that increa
5 min read
Tuple Relational Calculus (TRC) in DBMSTuple Relational Calculus (TRC) is a non-procedural query language used in relational database management systems (RDBMS) to retrieve data from tables. TRC is based on the concept of tuples, which are ordered sets of attribute values that represent a single row or record in a database table. TRC is
4 min read
Domain Relational Calculus in DBMSDomain Relational Calculus is a non-procedural query language equivalent in power to Tuple Relational Calculus. Domain Relational Calculus provides only the description of the query but it does not provide the methods to solve it. In Domain Relational Calculus, a query is expressed as, { < x1, x2
2 min read
Functional Dependencies & Normalization
Functional Dependency and Attribute ClosureFunctional dependency and attribute closure are essential for maintaining data integrity and building effective, organized, and normalized databases.Functional DependencyA functional dependency A->B in a relation holds if two tuples having the same value of attribute A must have the same value fo
5 min read
Armstrong's Axioms in Functional Dependency in DBMSArmstrong's Axioms refer to a set of inference rules, introduced by William W. Armstrong, that are used to test the logical implication of functional dependencies. Given a set of functional dependencies F, the closure of F (denoted as F+) is the set of all functional dependencies logically implied b
4 min read
Canonical Cover of Functional Dependencies in DBMSManaging a large set of functional dependencies can result in unnecessary computational overhead. This is where the canonical cover becomes useful. The canonical cover of a set of functional dependencies F is a simplified version of F that retains the same closure as the original set, ensuring no re
7 min read
Normal Forms in DBMSIn the world of database management, Normal Forms are important for ensuring that data is structured logically, reducing redundancy, and maintaining data integrity. When working with databases, especially relational databases, it is critical to follow normalization techniques that help to eliminate
7 min read
The Problem of Redundancy in DatabaseRedundancy means having multiple copies of the same data in the database. This problem arises when a database is not normalized. Suppose a table of student details attributes is: student ID, student name, college name, college rank, and course opted. Student_ID Name Contact College Course Rank 100Hi
6 min read
Lossless Join and Dependency Preserving DecompositionDecomposition of a relation is done when a relation in a relational model is not in appropriate normal form. Relation R is decomposed into two or more relations if decomposition is lossless join as well as dependency preserving. Lossless Join DecompositionIf we decompose a relation R into relations
4 min read
Denormalization in DatabasesDenormalization focuses on combining multiple tables to make queries execute quickly. It adds redundancies in the database though. In this article, weâll explore Denormalization and how it impacts database design. This method can help us to avoid costly joins in a relational database made during nor
6 min read
Transactions & Concurrency Control
ACID Properties in DBMSIn the world of DBMS, transactions are fundamental operations that allow us to modify and retrieve data. However, to ensure the integrity of a database, it is important that these transactions are executed in a way that maintains consistency, correctness, and reliability. This is where the ACID prop
8 min read
Types of Schedules in DBMSSchedule, as the name suggests, is a process of lining the transactions and executing them one by one. When there are multiple transactions that are running in a concurrent manner and the order of operation is needed to be set so that the operations do not overlap each other, Scheduling is brought i
7 min read
Recoverability in DBMSRecoverability is a critical feature of database systems. It ensures that after a failure, the database returns to a consistent state by permanently saving committed transactions and rolling back uncommitted ones. It relies on transaction logs to undo or redo changes as needed. This is crucial in mu
6 min read
Implementation of Locking in DBMSLocking protocols are used in database management systems as a means of concurrency control. Multiple transactions may request a lock on a data item simultaneously. Hence, we require a mechanism to manage the locking requests made by transactions. Such a mechanism is called a Lock Manager. It relies
5 min read
Deadlock in DBMSIn a Database Management System (DBMS), a deadlock occurs when two or more transactions are waiting indefinitely for one another to release resources (such as locks on tables, rows, or other database objects). This results in a situation where none of the transactions can proceed, effectively bringi
8 min read
Starvation in DBMSStarvation in DBMS is a problem that happens when some processes are unable to get the resources they need because other processes keep getting priority. This can happen in situations like locking or scheduling, where some processes keep getting the resources first, leaving others waiting indefinite
8 min read
Advanced DBMS
Indexing in Databases - Set 1Indexing is a crucial technique used in databases to optimize data retrieval operations. It improves query performance by minimizing disk I/O operations, thus reducing the time it takes to locate and access data. Essentially, indexing allows the database management system (DBMS) to locate data more
8 min read
Introduction of B-TreeA B-Tree is a specialized m-way tree designed to optimize data access, especially on disk-based storage systems. In a B-Tree of order m, each node can have up to m children and m-1 keys, allowing it to efficiently manage large datasets.The value of m is decided based on disk block and key sizes.One
8 min read
Introduction of B+ TreeB + Tree is a variation of the B-tree data structure. In a B + tree, data pointers are stored only at the leaf nodes of the tree. In this tree, structure of a leaf node differs from the structure of internal nodes. The leaf nodes have an entry for every value of the search field, along with a data p
8 min read
Bitmap Indexing in DBMSBitmap Indexing is a data indexing technique used in database management systems (DBMS) to improve the performance of read-only queries that involve large datasets. It involves creating a bitmap index, which is a data structure that represents the presence or absence of data values in a table or col
8 min read
Inverted IndexAn Inverted Index is a data structure used in information retrieval systems to efficiently retrieve documents or web pages containing a specific term or set of terms. In an inverted index, the index is organized by terms (words), and each term points to a list of documents or web pages that contain
7 min read
SQL Queries on Clustered and Non-Clustered IndexesIndexes in SQL play a pivotal role in enhancing database performance by enabling efficient data retrieval without scanning the entire table. The two primary types of indexes Clustered Index and Non-Clustered Index serve distinct purposes in optimizing query performance. In this article, we will expl
7 min read
File Organization in DBMS - Set 1A database consists of a huge amount of data. The data is grouped within a table in RDBMS, and each table has related records. A user can see that the data is stored in the form of tables, but in actuality, this huge amount of data is stored in physical memory in the form of files. What is a File?A
6 min read
DBMS Practice